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Aranha, Diego F.; FuentesCastañeda, Laura; Knapp, Edward; Menezes, Alfred; RodríguezHenríquez, Francisco
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14 Citations
We implement asymmetric pairings derived from KachisaSchaeferScott (KSS), BarretoNaehrig (BN), and BarretoLynnScott (BLS) elliptic curves at the 192bit security level. Somewhat surprisingly, we find pairings derived from BLS curves with embedding degree 12 to be the fastest for our serial as well as our parallel implementations. Our serial implementations provide a factor3 speedup over the previous stateoftheart, demonstrating that pairing computation at the 192bit security level is not as expensive as previously thought. We also present a general framework for deriving a Weiltype pairing that is wellsuited for computing a single pairing on a multiprocessor machine.
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Chakraborty, Debrup; Sarkar, Palash
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3 Citations
This work deals with the various requirements of encryption and authentication in cryptographic applications. The approach is to construct suitable modes of operations of a block cipher to achieve the relevant goals. A variety of schemes suitable for specific applications are presented. While none of the schemes are built completely from scratch, there is a common unifying framework which connects them. All the schemes described have been implemented and the implementation details are publicly available. Performance figures are presented when the block cipher is the AES and the Intel AESNI instructions are used. These figures suggest that the constructions presented here compare well with previous works such as the famous OCB mode of operation. In terms of features, the constructions provide several new offerings which are not present in earlier works. This work significantly widens the range of choices of an actual designer of cryptographic system.
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Aranha, Diego F.; Knapp, Edward; Menezes, Alfred; RodríguezHenríquez, Francisco
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4 Citations
In the past year, the speed record for pairing implementations on desktopclass machines has been broken several times. The speed records for asymmetric pairings were set on a single processor. In this paper, we describe our parallel implementation of the optimal ate pairing over BarretoNaehrig (BN) curves that is about 1.23 times faster using two cores of an Intel Core i5 or Core i7 machine, and 1.45 times faster using 4 cores of the Core i7 than the stateoftheart implementation on a single core. We instantiate Hess’s general Weil pairing construction and introduce a new optimal Weil pairing tailored for parallel execution. Our experimental results suggest that the new Weil pairing is 1.25 times faster than the optimal ate pairing on 8core extensions of the aforementioned machines. Finally, we combine previous techniques for parallelizing the eta pairing on a supersingular elliptic curve with embedding degree 4, and achieve an estimated 1.24fold speedup on an 8core extension of an Intel Core i7 over the previous best technique.
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FazHernández, Armando; Longa, Patrick; Sánchez, Ana H.
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12 Citations
We propose efficient algorithms and formulas that improve the performance of sidechannel protected scalar multiplication exploiting the GallantLambertVanstone (CRYPTO 2001) and GalbraithLinScott (EUROCRYPT 2009) methods. Firstly, by adapting Feng et al.’s recoding to the GLV setting, we derive new regular algorithms for variablebase scalar multiplication that offer protection against simple sidechannel and timing attacks. Secondly, we propose an efficient technique that interleaves ARMbased and NEONbased multiprecision operations over an extension field, as typically found on GLS curves and pairing computations, to improve performance on modern ARM processors. Finally, we showcase the efficiency of the proposed techniques by implementing a stateoftheart GLVGLS curve in twisted Edwards form defined over
$\mathbb{F}_{p^2}$
, which supports a four dimensional decomposition of the scalar and runs in constant time, i.e., it is fully protected against timing attacks. For instance, using a precomputed table of only 512 bytes, we compute a variablebase scalar multiplication in 92,000 cycles on an Intel Ivy Bridge processor and in 244,000 cycles on an ARM CortexA15 processor. Our benchmark results and the proposed techniques contribute to the improvement of the stateoftheart performance of elliptic curve computations. Most notably, our techniques allow us to reduce the cost of adding protection against timing attacks in the GLVbased variablebase scalar multiplication computation to below 10%.
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Adj, Gora; Menezes, Alfred; Oliveira, Thomaz; RodríguezHenríquez, Francisco
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2 Citations
We show that a Magma implementation of Joux’s
$$L[1/4+o(1)]$$
algorithm can be used to compute discrete logarithms in the 1303bit finite field
$${\mathbb F}_{3^{6 \cdot 137}}$$
and the 1551bit finite field
$${\mathbb F}_{3^{6 \cdot 163}}$$
with very modest computational resources. Our
$${\mathbb F}_{3^{6 \cdot 137}}$$
implementation was the first to illustrate the effectiveness of Joux’s algorithm for computing discrete logarithms in smallcharacteristic finite fields that are not Kummer or twistedKummer extensions.
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By
Chakraborty, Debrup; Nandi, Mridul
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5 Citations
HCTR was proposed by Wang, Feng and Wu in 2005. It is a mode of operation which provides a tweakable strong pseudorandom permutation. Though HCTR is quite an efficient mode, the authors showed a cubic security bound for HCTR which makes it unsuitable for applications where tweakable strong pseudorandom permutations are required. In this paper we show that HCTR has a better security bound than what the authors showed. We prove that the distinguishing advantage of an adversary in distinguishing HCTR and its inverse from a random permutation and its inverse is bounded above by 4.5 σ^{2}/2^{n}, where n is the blocklength of the blockcipher and σ is the number of nblock queries made by the adversary (including the tweak).
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By
FuentesCastañeda, Laura; Knapp, Edward; RodríguezHenríquez, Francisco
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7 Citations
An asymmetric pairing
$e\colon{\mathbb{G}}_2\times{\mathbb{G}}_1\to{\mathbb{G}}_T$
is considered such that
${\mathbb{G}}_1=E({\mathbb F}_p)[r]$
and
${\mathbb{G}}_2=\tilde E({\mathbb F}_{p^{k/d}})[r]$
, where k is the embedding degree of the elliptic curve
$E/{\mathbb F}_p$
, r is a large prime divisor of
$\# E({\mathbb F}_p)$
, and
$\tilde E$
is the degreed twist of E over
${\mathbb F}_{p^{k/d}}$
with
$r \mid \tilde E ({\mathbb F}_{p^{k/d}} )$
. Hashing to
${\mathbb{G}}_1$
is considered easy, while hashing to
${\mathbb{G}}_2$
is done by selecting a random point Q in
$\tilde E({\mathbb F}_{p^{k/d}})$
and computing the hash value cQ, where c·r is the order of
$\tilde E({\mathbb F}_{p^{k/d}})$
. We show that for a large class of curves, one can hash to
${\mathbb{G}}_2$
in
$\textup{O}(1/\varphi (k)\log c)$
time, as compared with the previously fastestknown
$\textup{O}(\log p)$
. In the case of BN curves, we are able to double the speed of hashing to
${\mathbb{G}}_2$
. For higherembeddingdegree curves, the results can be more dramatic. We also show how to reduce the cost of the finalexponentiation step in a pairing calculation by a fixed number of field multiplications.
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By
Coello, Carlos A. Coello
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This chapter provides a short overview of multiobjective optimization using metaheuristics. The chapter includes a description of some of the main metaheuristics that have been used for multiobjective optimization. Although special emphasis is made on evolutionary algorithms, other metaheuristics, such as particle swarm optimization, artificial immune systems, and ant colony optimization, are also briefly discussed. Other topics such as applications and recent algorithmic trends are also included. Finally, some of the main research trends that are worth exploring in this area are briefly discussed.
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Adj, Gora; Menezes, Alfred; Oliveira, Thomaz; RodríguezHenríquez, Francisco
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3 Citations
In 2013, Joux, and then Barbulescu, Gaudry, Joux and Thomé, presented new algorithms for computing discrete logarithms in finite fields of small and medium characteristic. We show that these new algorithms render the finite field
${\mathbb{F}}_{3^{6 \cdot 509}} = {\mathbb{F}}_{3^{3054}}$
weak for discrete logarithm cryptography in the sense that discrete logarithms in this field can be computed significantly faster than with the previous fastest algorithms. Our concrete analysis shows that the supersingular elliptic curve over
${\mathbb{F}}_{3^{509}}$
with embedding degree 6 that had been considered for implementing pairingbased cryptosystems at the 128bit security level in fact provides only a significantly lower level of security. Our work provides a convenient framework and tools for performing a concrete analysis of the new discrete logarithm algorithms and their variants.
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By
Taverne, Jonathan; FazHernández, Armando; Aranha, Diego F.; RodríguezHenríquez, Francisco; Hankerson, Darrel; López, Julio
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6 Citations
The availability of a new carryless multiplication instruction in the latest Intel desktop processors significantly accelerates multiplication in binary fields and hence presents the opportunity for reevaluating algorithms for binary field arithmetic and scalar multiplication over elliptic curves. We describe how to best employ this instruction in field multiplication and the effect on performance of doubling and halving operations. Alternate strategies for implementing inversion and halftrace are examined to restore most of their competitiveness relative to the new multiplier. These improvements in field arithmetic are complemented by a study on serial and parallel approaches for Koblitz and random curves, where parallelization strategies are implemented and compared. The contributions are illustrated with experimental results improving the stateoftheart performance of halving and doublingbased scalar multiplication on NIST curves at the 112 and 192bit security levels, and a new speed record for sidechannel resistant scalar multiplication in a random curve at the 128bit security level.
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By
Oliveira, Thomaz; López, Julio; Aranha, Diego F.; RodríguezHenríquez, Francisco
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7 Citations
In this work we present the λcoordinates, a new system for representing points in binary elliptic curves. We also provide efficient elliptic curve operations based on the new representation and timing results of our software implementation over the field
$\mathbb{F}_{2^{254}}$
. As a result, we improve speed records for protected/unprotected single/multicore software implementations of randompoint elliptic curve scalar multiplication at the 128bit security level. When implemented on a Sandy Bridge 3.4GHz Intel Xeon processor, our software is able to compute a single/multicore unprotected scalar multiplication in 72,300 and 47,900 clock cycles, respectively; and a protected singlecore scalar multiplication in 114,800 cycles. These numbers improve by around 2% on the newer Core i7 2.8GHz Ivy Bridge platform.
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By
Coello, Carlos A. Coello
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This chapter provides a short overview of multiobjective optimization using metaheuristics. The chapter includes a description of some of the main metaheuristics that have been used for multiobjective optimization. Although special emphasis is made on evolutionary algorithms, other metaheuristics, such as particle swarm optimization, artificial immune systems, and ant colony optimization, are also briefly discussed. Other topics such as applications and recent algorithmic trends are also included. Finally, some of the main research trends that are worth exploring in this area are briefly discussed.
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By
Aranha, Diego F.; FazHernández, Armando; López, Julio; RodríguezHenríquez, Francisco
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8 Citations
We design a stateoftheart software implementation of field and elliptic curve arithmetic in standard Koblitz curves at the 128bit security level. Field arithmetic is carefully crafted by using the best formulae and implementation strategies available, and the increasingly common native support to binary field arithmetic in modern desktop computing platforms. The ith power of the Frobenius automorphism on Koblitz curves is exploited to obtain new and faster interleaved versions of the wellknown τNAF scalar multiplication algorithm. The usage of the
$\tau^{\lfloor m/3 \rfloor}$
and
$\tau^{\lfloor m/4 \rfloor}$
maps are employed to create analogues of the 3and 4dimensional GLV decompositions and in general, the
$\lfloor m/s \rfloor$
th power of the Frobenius automorphism is applied as an analogue of an sdimensional GLV decomposition. The effectiveness of these techniques is illustrated by timing the scalar multiplication operation for fixed, random and multiple points. In particular, our library is able to compute a random point scalar multiplication in just below 10^{5} clock cycles, which sets a new speed record across all curves with or without endomorphisms defined over binary or prime fields. The results of our optimized implementation suggest a tradeoff between speed, compliance with the published standards and sidechannel protection. Finally, we estimate the performance of curvebased cryptographic protocols instantiated using the proposed techniques and compare our results to related work.
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By
Oliveira, Thomaz; Aranha, Diego F.; López, Julio; RodríguezHenríquez, Francisco
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6 Citations
In this paper we introduce new methods for computing constanttime variablebase point multiplications over the GalbraithLinScott (GLS) and the Koblitz families of elliptic curves. Using a lefttoright doubleandadd and a righttoleft halveandadd Montgomery ladder over a GLS curve, we present some of the fastest timings yet reported in the literature for point multiplication. In addition, we combine these two procedures to compute a multicore protected scalar multiplication. Furthermore, we designed a novel regular
$$\tau $$
adic scalar expansion for Koblitz curves. As a result, using the regular recoding approach, we set the speed record for a singlecore constanttime point multiplication on standardized binary elliptic curves at the
$$128$$
bit security level.
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By
Chi, JesúsJavier; Oliveira, Thomaz
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1 Citations
In this paper we present a complete Magma implementation for solving the discrete logarithm problem (DLP) on a binary GLS curve defined over the field
$$\mathbb {F}_{2^{62}}$$
. For this purpose, we constructed a curve vulnerable against the gGHS Weil descent attack and adapted the algorithm proposed by Enge and Gaudry to solve the DLP on the Jacobian of a genus32 hyperelliptic curve. Furthermore, we describe a mechanism to check whether a randomly selected binary GLS curve is vulnerable against the gGHS attack. Such method works with all curves defined over binary fields and can be applied to each element of the isogeny class.
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By
Chang, Donghoon; Nandi, Mridul
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9 Citations
The classical design principle MerkleDamgård [13,6] is scrutinized by many ways such as Joux’s multicollision attack, KelseySchneier second preimage attack etc. In TCC’04, Maurer et al. introduced a strong security notion called as “indifferentiability” for a hash function based on a compression function. The classical design principle is also insecure against this strong security notion whereas chopMD hash is secure with the security bound roughly σ^{2}/2^{s} where s is the number of chopped bits and σ is the total number of message blocks queried by a distinguisher. In case of n = 2s where n is the output size of a compression function, the value σ to get a significant bound is 2^{s/2} which is the birthday complexity, where the hash output size is sbit. In this paper, we present an improved security bound for chopMD. The improved bound shown in this paper is (3(n − s) + 1)q/2^{s} + q/2^{n − s − 1} + σ^{2}/2^{n + 1} where q is the total number of queries. In case of n = 2s, chopMD is indifferentiablysecure if q = O(2^{s}/(3s + 1)) and σ = O(2^{n/2}) which are beyond the birthday complexity. We also present a design principle for an nbit hash function based on a compression function
$f : {0,1}^{2n+b} {\Rightarrow} {0,1}^n$
and show that the indifferentiability security bound for this hash function is roughly (3n + 1)σ/2^{n}. So, the new design of hash function is secondpreimage and rmulticollision secure as long as the query complexity (the number of message blocks queried) of an attacker is less than 2^{n}/(3n + 1) or 2^{n(r − 1)/r} respectively.
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By
MoralesLuna, Guillermo
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1 Citations
We use a simple epistemic logic to pose problems related to relational database design. We use the notion of attribute dependencies, which is weaker than the notion of functional dependencies, to perform design tasks since it satisfies Armstrong axioms. We discuss also the application of the simple epistemic logic to privacy protection and to statistical disclosure.
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By
Picek, Stjepan; Coello Coello, Carlos A.; Jakobovic, Domagoj; Mentens, Nele
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2 Citations
The problem of finding the shortest addition chain for a given exponent is of great relevance in cryptography, but is also very difficult to solve since it is an NPhard problem. In this paper, we propose a genetic algorithm with a novel representation of solutions and new crossover and mutation operators to minimize the length of the addition chains corresponding to a given exponent. We also develop a repair strategy that significantly enhances the performance of our approach. The results are compared with respect to those generated by other metaheuristics for instances of moderate size, but we also investigate values up to
$$2^{127}  3$$
. For those instances, we were unable to find any results produced by other metaheuristics for comparison, and three additional strategies were adopted in this case to serve as benchmarks. Our results indicate that the proposed approach is a very promising alternative to deal with this problem.
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By
Sánchez, Ana Helena; RodríguezHenríquez, Francisco
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7 Citations
In 2011, Waters presented a ciphertextpolicy attribute based encryption protocol that uses bilinear pairings to provide control access mechanisms, where the set of user’s attributes is specified by means of a linear secret sharing scheme. Some of the applications foreseen for this protocol lie in the context of mobile devices such a smartphones and tablets, which in a majority of instances are powered by an ARM processor supporting the NEON vector set of instructions. In this paper we present the design of a software cryptographic library that implements a 127bit security level attributebased encryption scheme over mobile devices equipped with a 1.4GHz Exynos 4 CortexA9 processor and a developing board that hosts a 1.7 GHz Exynos 5 CortexA15 processor. For the latter platform and taking advantage of the inherent parallelism of the NEON vector instructions, our library computes a single optimal pairing over a BarretoNaehrig curve approximately 2 times faster than the best timings previously reported on ARM platforms at this level of security. Further, using a 6attribute access formula our library is able to encrypt/decrypt a text/ciphertext in less than 7.5mS and 15.67mS, respectively.
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By
Adj, Gora; CervantesVázquez, Daniel; ChiDomínguez, JesúsJavier; Menezes, Alfred; RodríguezHenríquez, Francisco
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The security of the JaoDe Feo Supersingular Isogeny DiffieHellman (SIDH) key agreement scheme is based on the intractability of the Computational Supersingular Isogeny (CSSI) problem—computing
$${\mathbb F}_{p^2}$$
rational isogenies of degrees
$$2^e$$
and
$$3^e$$
between certain supersingular elliptic curves defined over
$${\mathbb F}_{p^2}$$
. The classical meetinthemiddle attack on CSSI has an expected running time of
$$O(p^{1/4})$$
, but also has
$$O(p^{1/4})$$
storage requirements. In this paper, we demonstrate that the van OorschotWiener golden collision finding algorithm has a lower cost (but higher running time) for solving CSSI, and thus should be used instead of the meetinthemiddle attack to assess the security of SIDH against classical attacks. The smaller parameter p brings significantly improved performance for SIDH.
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By
Pierrard, Thomas; Coello Coello, Carlos A.
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3 Citations
This paper presents a new artificial immune system algorithm for solving multiobjective optimization problems, based on the clonal selection principle and the hypervolume contribution. The main aim of this work is to investigate the performance of this class of algorithm with respect to approaches which are representative of the stateoftheart in multiobjective optimization using metaheuristics. The results obtained by our proposed approach, called multiobjective artificial immune system based on hypervolume (MOAISHV) are compared with respect to those of the NSGAII. Our preliminary results indicate that our proposed approach is very competitive, and can be a viable choice for solving multiobjective optimization problems.
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By
Chakraborty, Debrup; Sarkar, Palash
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13 Citations
The notion and the first construction of a tweakable enciphering scheme, called CMC, was presented by HaleviRogaway at Crypto 2003. In this paper, we present HCH, which is a new construction of such a scheme. The construction uses the hashencrypthash approach introduced by NaorReingold. This approach has recently been used in the constructions of tweakable enciphering schemes HCTR and PEP. HCH has several advantages over the previous schemes CMC, EME, EME*, HCTR, and PEP. CMC, EME, and EME* use two blockcipher invocations per message block, while HCTR, PEP, and HCH use only one. PEP uses four multiplications per block, while HCTR and HCH use only two. In HCTR, the security bound is cubic, while in HCH security bound is quadratic.
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By
Taverne, Jonathan; FazHernández, Armando; Aranha, Diego F.; RodríguezHenríquez, Francisco; Hankerson, Darrel; López, Julio
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13 Citations
The availability of a new carryless multiplication instruction in the latest Intel desktop processors significantly accelerates multiplication in binary fields and hence presents the opportunity for reevaluating algorithms for binary field arithmetic and scalar multiplication over elliptic curves. We describe how to best employ this instruction in field multiplication and the effect on performance of doubling and halving operations. Alternate strategies for implementing inversion and halftrace are examined to restore most of their competitiveness relative to the new multiplier. These improvements in field arithmetic are complemented by a study on serial and parallel approaches for Koblitz and random curves, where parallelization strategies are implemented and compared. The contributions are illustrated with experimental results improving the stateoftheart performance of halving and doublingbased scalar multiplication on NIST curves at the 112 and 192bit security levels and a new speed record for sidechannelresistant scalar multiplication in a random curve at the 128bit security level. The algorithms presented in this work were implemented on Westmere and Sandy Bridge processors, the latest generation Intel microarchitectures.
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By
Adj, Gora; CanalesMartínez, Isaac; RiveraZamarripa, Luis; RodríguezHenríquez, Francisco
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The problem of determining whether a polynomial defined over a finite field ring is smooth or not with respect to a given degree, is the most intensive arithmetic operation of the socalled descent phase of indexcalculus algorithms. In this paper, we present an analysis and efficient implementation of Coppersmith’s smoothness test for polynomials defined over finite fields with characteristic three. As a case study, we review the best strategies for obtaining a fast field and polynomial arithmetic for polynomials defined over the ring
$$F_q[X],$$
with
$$q=3^6,$$
and report the timings achieved by our library when computing the smoothness test applied to polynomials of several degrees defined in that ring. This software library was recently used in Adj et al. (Cryptology 2016.
http://eprint.iacr.org/2016/914
), as a building block for achieving a record computation of discrete logarithms over the 4841bit field
$${{\mathbb {F}}}_{3^{6\cdot 509}}$$
.
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By
Molinet Berenguer, José A.; Coello Coello, Carlos A.
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1 Citations
In this paper, we propose a new multiobjective evolutionary algorithm (MOEA), which transforms a multiobjective optimization problem into a linear assignment problem using a set of weight vectors uniformly scattered. Our approach adopts uniform design to obtain the set of weights and KuhnMunkres’ (Hungarian) algorithm to solve the assignment problem. Differential evolution is used as our search engine, giving rise to the socalled Hungarian Differential Evolution algorithm (HDE). Our proposed approach is compared with respect to a MOEA based on decomposition (MOEA/D) and with respect to an indicatorbased MOEA (the S metric selection Evolutionary MultiObjective Algorithm, SMS EMOA) using several test problems (taken from the specialized literature) having from two to ten objective functions. Our preliminary experimental results indicate that our proposed HDE outperforms MOEA/D and is competitive with respect to SMSEMOA, but at a significantly lower computational cost.
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By
Korjik, Valeri; MoralesLuna, Guillermo
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1 Citations
We consider a scenario where information hiding (IH) is performed through noisy channels. There may arise different situations but one of the most common is the case where the legal IH channel is superior to the attacker IH channel. If a special randomized encoding is used by legal users then it is possible to hide information in the noisy components of the cover message. At the same time, the randomized encoding prevents the secret message to be removed from the stegomessage without any significant distortion of the cover message. If a legal decoder of IH knows the cover message, a randomized encoding procedure does not prevent the error correction of the secret message at the receiving side. The special problem of IH  how to distinguish any binary periodic repetitive sequence from truly random binary noise received on noisy channels  is presented. Application of the randomized encoding technique makes a solution to this problem more difficult and hence complicates a traffic analysis. We consider also how is it possible to “camouflage” IH by natural channel noises independently of the properties of the cover messages probability space, and the application of WM in combination with randomized encoding dedicated to the utilization of noisy channels. If an attacker tries to remove WM by adding binary noise then an expansion of errors in the cover message results.
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By
Arias Montaño, Alfredo; Coello Coello, Carlos A.; MezuraMontes, Efrén
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This paper introduces a novel Parallel MultiObjective Evolutionary Algorithm (pMOEA) which is based on the island model. The serial algorithm on which this approach is based uses the differential evolution operators as its search engine, and includes two mechanisms for improving its convergence properties (through local dominance and environmental selection based on scalar functions). Two different parallel approaches are presented. The first aims at improving effectiveness (i.e., for better approximating the Pareto front) while the second aims to provide a better efficiency (i.e., by reducing the execution time through the use of small population sizes in each subpopulation). To assess the performance of the proposed algorithms, we adopt a set of standard test functions and performance measures taken from the specialized literature. Results are compared with respect to its serial counterpart and with respect to three algorithms representative of the stateoftheart in the area: NSGAII, MOEA/D and MOEA/DDE.
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By
RodríguezHenríquez, Lil María; Chakraborty, Debrup
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Security of outsourced databases is an important problem of current practical interest. In this paper we address the problem of authenticated query processing in outsourced databases. We describe the syntax of a generic scheme for authenticated query processing called RDAS, and provide security definitions for RDAS in line with concrete provable security. Then, we propose a new scheme called RDAS1 which enables a client to ensure both correctness and completeness of the query results obtained from a server. Our solution involves use of bitmap indices and message authentication codes in a novel manner. We prove that RDAS1 is secure relative to our security definition. Finally, we discuss a concrete improvement over RDAS1 (which we call RDAS2) and provide performance data for both RDAS1 and RDAS2 on a real data base.
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By
Oliveira, Thomaz; López, Julio; RodríguezHenríquez, Francisco
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3 Citations
In this work, we retake an old idea presented by Koblitz in his landmark paper [21], where he suggested the possibility of defining anomalous elliptic curves over the base field
$$\mathbb {F}_4$$
. We present a careful implementation of the base and quadratic field arithmetic required for computing the scalar multiplication operation in such curves. In order to achieve a fast reduction procedure, we adopted a redundant trinomial strategy that embeds elements of the field
$$\mathbb {F}_{4^{m}},$$
with m a prime number, into a ring of higher order defined by an almost irreducible trinomial. We also report a number of techniques that allow us to take full advantage of the native vector instructions of highend microprocessors. Our software library achieves the fastest timings reported for the computation of the timingprotected scalar multiplication on Koblitz curves, and competitive timings with respect to the speed records established recently in the computation of the scalar multiplication over prime fields.
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By
Salomon, Shaul; Avigad, Gideon; Goldvard, Alex; Schütze, Oliver
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6 Citations
It has generally been acknowledged that both proximity to the Pareto front and a certain diversity along the front should be targeted when using evolutionary algorithms to evolve solutions to multiobjective optimization problems. Although many evolutionary algorithms are equipped with mechanisms to achieve both targets, most give priority to proximity over diversity. This priority is embedded within the algorithms through the selection of solutions to the elite population based on the concept of dominance. Although the current study does not change this embedded preference, it does utilize an improved diversity preservation mechanism that is based on a recently introduced partitioning algorithm for function selection. It is shown that this partitioning allows for the selection of a welldiversified set out of an arbitrary given set. Further, when embedded into an evolutionary search, this procedure significantly enhances the exploitation of diversity. The procedure is demonstrated on commonly used test cases for up to five objectives. The potential for further improving evolutionary algorithms through the use of the partitioning algorithm is highlighted.
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By
Durillo, Juan J.; GarcíaNieto, José; Nebro, Antonio J.; Coello, Carlos A. Coello; Luna, Francisco; Alba, Enrique
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47 Citations
Particle Swarm Optimization (PSO) has received increasing attention in the optimization research community since its first appearance in the mid1990s. Regarding multiobjective optimization, a considerable number of algorithms based on MultiObjective Particle Swarm Optimizers (MOPSOs) can be found in the specialized literature. Unfortunately, no experimental comparisons have been made in order to clarify which MOPSO version shows the best performance. In this paper, we use a benchmark composed of three wellknown problem families (ZDT, DTLZ, and WFG) with the aim of analyzing the search capabilities of six representative stateoftheart MOPSOs, namely, NSPSO, SigmaMOPSO, OMOPSO, AMOPSO, MOPSOpd, and CLMOPSO. We additionally propose a new MOPSO algorithm, called SMPSO, characterized by including a velocity constraint mechanism, obtaining promising results where the rest perform inadequately.
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By
Nebro, Antonio Jesús; Durillo, Juan José; Coello Coello, Carlos A.; Luna, Francisco; Alba, Enrique
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13 Citations
An open issue in multiobjective optimization is designing metaheuristics that reach the Pareto front using a low number of function evaluations. In this paper, we adopt a benchmark composed of three wellknown problem families (ZDT, DTLZ, and WFG) and analyze the behavior of six stateoftheart multiobjective metaheuristics, namely, NSGAII, SPEA2, PAES, OMOPSO, AbYSS, and MOCell, according to their convergence speed, i.e., the number of evaluations required to obtain an accurate Pareto front. By using the hypervolume as a quality indicator, we measure the algorithms converging faster, as well as their hit rate over 100 independent runs. Our study reveals that modern multiobjective metaheuristics such as MOCell, OMOPSO, and AbYSS provide the best overall performance, while NSGAII and MOCell achieve the best hit rates.
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By
Hernández, Víctor Adrián Sosa; Schütze, Oliver; Trautmann, Heike; Rudolph, Günter
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In this paper we investigate some aspects of stochastic local search such as pressure toward and along the set of interest within parameter dependent multiobjective optimization problems. The discussions and initial computations indicate that the problem to compute an approximation of the entire solution set of such a problem via stochastic search algorithms is wellconditioned. The new insights may be helpful for the design of novel stochastic search algorithms such as specialized evolutionary approaches. The discussion in particular indicates that it might be beneficial to integrate the set of external parameters directly into the search instead of computing projections of the solution sets separately by fixing the value of the external parameter.
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Cabrera, Juan Carlos Fuentes; Coello, Carlos A. Coello
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7 Citations
In this chapter, we present a multiobjective evolutionary algorithm (MOEA) based on the heuristic called “particle swarm optimization” (PSO). This multiobjective particle swarm optimizer (MOPSO) is characterized for using a very small population size, which allows it to require a very low number of objective function evaluations (only 3000 per run) to produce reasonably good approximations of the Pareto front of problems of moderate dimensionality. The proposed approach first selects the leader and then selects the neighborhood for integrating the swarm. The leader selection scheme adopted is based on Pareto dominance and uses a neighbors density estimator. Additionally, the proposed approach performs a reinitialization process for preserving diversity and uses two external archives: one for storing the solutions that the algorithm finds during the search process and another for storing the final solutions obtained. Furthermore, a mutation operator is incorporated to improve the exploratory capabilities of the algorithm. The proposed approach is validated using standard test functions and performance measures reported in the specialized literature. Our results are compared with respect to those generated by the Nondominated Sorting Genetic Algorithm II (NSGAII), which is a MOEA representative of the stateoftheart in the area.
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Chakraborty, Debrup; López, Cuauhtemoc Mancillas; Sarkar, Palash
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1 Citations
In the last one and a half decade there has been a lot of activity toward development of cryptographic techniques for disk encryption. It has been almost canonized that an encryption scheme suitable for the application of disk encryption must be length preserving, i.e., it rules out the use of schemes such as authenticated encryption where an authentication tag is also produced as a part of the ciphertext resulting in ciphertexts being longer than the corresponding plaintexts. The notion of a tweakable enciphering scheme (TES) has been formalized as the appropriate primitive for disk encryption, and it has been argued that they provide the maximum security possible for a tagless scheme. On the other hand, TESs are less efficient than some existing authenticated encryption schemes. Also TES cannot provide true authentication as they do not have authentication tags. In this paper, we analyze the possibility of the use of encryption schemes where length expansion is produced for the purpose of disk encryption. On the negative side, we argue that noncebased authenticated encryption schemes are not appropriate for this application. On the positive side, we demonstrate that deterministic authenticated encryption (DAE) schemes may have more advantages than disadvantages compared to a TES when used for disk encryption. Finally, we propose a new deterministic authenticated encryption scheme called BCTR which is suitable for this purpose. We provide the full specification of BCTR, prove its security and also report an efficient implementation in reconfigurable hardware. Our experiments suggests that BCTR performs significantly better than existing TESs and existing DAE schemes.
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López Jaimes, Antonio; Coello Coello, Carlos A.; Aguirre, Hernán; Tanaka, Kiyoshi
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5 Citations
In a previous work we proposed a scheme for partitioning the objective space using the conflict information of the current Pareto front approximation found by an underlying multiobjective evolutionary algorithm. Since that scheme introduced additional parameters that have to be set by the user, in this paper we propose important modifications in order to automatically set those parameters. Such parameters control the number of solutions devoted to explore each objective subspace, and the number of generations to create a new partition. Our experimental results show that the new adaptive scheme performs as good as the nonadaptive scheme, and in some cases it outperforms the original scheme.
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OlmedoAguirre, José Oscar; Rosa, Mónica Rivera; MoralesLuna, Guillermo
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System modeling, analysis and visualization are becoming a common practice for the design of distributed intelligent systems since the wide adoption of the Unified Modeling Language (UML). However, UML cannot describe important behavioral properties such as context awareness as required for ubiquitous computing. In this paper, we present Context Aware UML Sequence diagrams (CA UMLS), an experimental visual programming language that extends UML sequence diagrams with data/ object spaces to represent computational context awareness. The programming language provides the means to describe the eventconditionaction (ECA) rules that govern complex nomadic user behavior and to visualize their effect. The ECA rules are compiled into common concurrent programming abstractions by introducing structuring notions of object creation, synchronization, and communication, along with sequential and selective composition of simpler rules. The contribution of this work is in providing programming abstractions that facilitate the design of contextaware applications for ubiquitous and nomadic computing.
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FalcónCardona, Jesús Guillermo; Coello Coello, Carlos A.
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Recently, it has been shown that the current ManyObjective Evolutionary Algorithms (MaOEAs) are overspecialized in solving certain benchmark problems. This overspecialization is due to a high correlation between the Pareto fronts of the test problems with the convex weight vectors commonly used by MaOEAs. The main consequence of such overspecialization is the inability of these MaOEAs to solve the minus versions of wellknown benchmarks (e.g., the DTLZ
$$^{1}$$
test suite). In furtherance of avoiding this issue, we propose a novel steadystate MaOEA that does not require weight vectors and uses a density estimator based on the IGD
$$^+$$
indicator. Moreover, a fast method to calculate the IGD
$$^+$$
contributions is integrated in order to reduce the computational cost of the proposed approach, which is called IGD
$$^+$$
MaOEA. Our proposed approach is compared with NSGAIII, MOEA/D, IGD
$$^+$$
EMOA (the previous ones employ convex weight vectors) and SMSEMOA on the test suites DTLZ and DTLZ
$$^{1}$$
, using the hypervolume indicator. Our experimental results show that IGD
$$^+$$
MaOEA is a more general optimizer than MaOEAs that need a set of convex weight vectors and it is competitive and less computational expensive than SMSEMOA.
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Sharmeen, Zahra; MartinezEnriquez, Ana Maria; Aslam, Muhammad; Syed, Afraz Zahra; Waheed, Talha
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2 Citations
Natural disasters cause devastation in the society due to unpredictable nature. Whether damage is minor or severe, emergency support should be provided within time. Multiagent systems have been proposed to efficiently cope with emergency situations. Lot of work has been done on maturing core functionality of these systems but little attention has been given to their user interface. The world is moving towards an era where humans and machines work together to complete complex tasks. Management of such emergent situations is improved by combining superior human intelligence with efficiency of multiagent systems. Our goal is to design and develop agents based interface that facilitates humans not only in operating the system but also in resource mobilization like ambulances, fire brigade, etc. to reduce life and property loss. This enhancement improves system adaptability and speeds up the relief operation by saving time of humanagent consumed in dealing with complex computer interface.
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Lara, Adriana; Schütze, Oliver; Coello Coello, Carlos A.
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4 Citations
Using evolutionary algorithms when solving multiobjective optimization problems (MOPs) has shown remarkable results during the last decade. As a consolidated research area it counts with a number of guidelines and processes; even though, their efficiency is still a big issue which lets room for improvements. In this chapter we explore the use of gradientbased information to increase efficiency on evolutionary methods, when dealing with smooth realvalued MOPs. We show the main aspects to be considered when building local search operators using the objective function gradients, and when coupling them with evolutionary algorithms. We present an overview of our current methods with discussion about their convenience for particular kinds of problems.
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Rodríguez, Lisbeth; Li, Xiaoou; MejíaAlvarez, Pedro
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2 Citations
Vertical partitioning is a well known technique to improve query response time in relational databases. This consists in dividing a table into a set of fragments of attributes according to the queries run against the table. In dynamic systems the queries tend to change with time, so it is needed a dynamic vertical partitioning technique which adapts the fragments according to the changes in query patterns in order to avoid long query response time. In this paper, we propose an active system for dynamic vertical partitioning of relational databases, called DYVEP (DYnamic VErtical Partitioning). DYVEP uses active rules to vertically fragment and refragment a database without intervention of a database administrator (DBA), maintaining an acceptable query response time even when the query patterns in the database suffer changes. Experiments with the TPCH benchmark demonstrate efficient query response time.
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Bravo, Maricela; Rodríguez, José; Reyes, Alejandro
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1 Citations
Service Oriented Computing (SOC) has incrementally been adopted as the preferred programming paradigm for the development, integration and interoperation of large and complex information systems. However, despite its increasing popularity, the SOC has not achieved its full potential yet. This is mainly due to the lack of supporting tools to enrich and represent semantically Web service descriptions. This paper describes a solution approach for the automatic representation of Web service descriptions and their further semantic enrichment between operation names based on the calculation of four semantic similarity measures. The enrichment approach is accurate because the final decision is done through a voting scheme, in the case of inconsistent results, these are not asserted into the ontology. Experimentation shows that although few similarity relationships are found and asserted, they represent an important step towards the automatic discovery of information that was previously unknown.
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Wang, Jiacun; Tepfenhart, Bill; Li, Xiaoou
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A workflow describes the flow of jobs of a business process. Executing a workflow requires resources. In many situations, business processes are constrained by scarce resources. Therefore, it is important to understand workflow resource requirement. In our previous work, we introduced resource oriented workflow nets (ROWN) and based on ROWN, an efficient algorithm for the analysis of the maximum resource requirement of a workflow (maxRR) was developed [11]. The maxRR is the minimum amount of resources that support workflow execution along every possible path. On the hand, when there is a resource shortage, it is important to find the minimum resource requirement (minRR), which is the minimum amount of resources that support workflow execution along at least one path. In this paper, we present an approach to analyzing the minRR.
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Mendoza, Sonia; Morán, Alberto L.; Decouchant, Dominique; Enríquez, Ana María Martínez; Favela, Jesus
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The PIÑAS platform provides an authoring group with support to collaboratively and consistently produce shared Web documents. Such documents may include costly multimedia resources, whose management raises important issues due to the constraints imposed by Web technology. This poster presents an approach for distributing shared Web documents to the authoring group’s sites, taking into consideration current organization of the concerned sites, access rights granted to the coauthors and storage device capabilities.
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Zapotecas Martínez, Saúl; Sosa Hernández, Víctor A.; Aguirre, Hernán; Tanaka, Kiyoshi; Coello Coello, Carlos A.
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5 Citations
The design of selection mechanisms based on quality assessment indicators has become one of the main research topics in the development of MultiObjective Evolutionary Algorithms (MOEAs). Currently, most indicatorbased MOEAs have employed the hypervolume indicator as their selection mechanism in the search process. However, hypervolumebased MOEAs become inefficient (and eventually, unaffordable) as the number of objectives increases. In this paper, we study the construction of a reference set from a family of curves. Such reference set is used together with a performance indicator (namely Δ_{p}) to assess the quality of solutions in the evolutionary process of an MOEA. We show that our proposed approach is able to deal (in an efficient way) with problems having many objectives (up to ten objective functions). Our preliminary results indicate that our proposed approach is highly competitive with respect to two stateoftheart MOEAs over the set of test problems that were adopted in our comparative study.
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Sandoval, Alejandro Cruz; Yu, Wen
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Dynamic neural networks with different timescales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of the designed network be stable. In this paper, the passivitybased approach is used to derive stability conditions for dynamic neural networks with different timescales. Several stability properties, such as passivity, asymptotic stability, inputtostate stability and bounded input bounded output stability, are guaranteed in certain senses. Numerical examples are also given to demonstrate the effectiveness of the theoretical results.
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Chakraborty, Debrup; HernandezJimenez, Vicente; Sarkar, Palash
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1 Citations
XCB is a tweakable enciphering scheme (TES) which was first proposed in 2004. The scheme was modified in 2007. We call these two versions of XCB as XCBv1 and XCBv2 respectively. XCBv2 was later proposed as a standard for encryption of sector oriented storage media in IEEEstd 1619.2 2010. There is no known proof of security for XCBv1 but the authors provided a concrete security bound for XCBv2 and a “proof” justifying the bound. In this paper we show that XCBv2 is not secure as a TES by showing an easy distinguishing attack on it. For XCBv2 to be secure, the message space should contain only messages whose lengths are multiples of the block length of the block cipher. Even for such restricted message spaces, the bound that the authors claim is not justified. We show this by pointing out some errors in the proof. For XCBv2 on full block messages, we provide a new security analysis. The resulting bound that can be proved is much worse than what has been claimed by the authors. Further, we provide the first concrete security bound for XCBv1, which holds for all message lengths. In terms of known security bounds, both XCBv1 and XCBv2 are worse compared to existing alternative TESs.
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RosalesPérez, Alejandro; Gonzalez, Jesus A.; CoelloCoello, Carlos A.; ReyesGarcia, Carlos A.; Escalante, Hugo Jair
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This paper introduces EMOPG+FS, a novel approach to prototype generation and feature selection that explicitly minimizes the classification error rate, the number of prototypes, and the number of features. Under EMOPG+FS, prototypes are initialized from a subset of training instances, whose positions are adjusted through a multiobjective evolutionary algorithm. The optimization process aims to find a set of suitable solutions that represent the best possible tradeoffs among the considered criteria. Besides this, we also propose a strategy for selecting a single solution from the several that are generated during the multiobjective optimization process.We assess the performance of our proposed EMOPG+FS using a suite of benchmark data sets and we compare its results with respect to those obtained by other evolutionary and nonevolutionary techniques. Our experimental results indicate that our proposed approach is able to achieve highly competitive results.
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Batool, Madeeha; Waqar, Mirza Muhammad; MartinezEnriquez, Ana Maria; Muhammad, Aslam
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Today, even in the presence of IT applications built for the blind, they are facing many problems. Either the applications are for individual’s use or if offer collaborative writing, they are not up to the mark. In the collaborative writing, for instance, in Microsoft Word AddIn and the Google Docs UI, the authors do not know about changes made in the document. Though the former facilitates this feature through adding comments in the document, but the dynamic actions, e.g. notifications (the user signin, editing the document, closing it) and communication option is yet to be considered. We describe a web application for the blind community to work on a shared document from different locations. Users are able to write, read, edit, and update the collaborative document in a controlled way. We aim to enhance the selfreliance among users and improve performance.
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GarzaFabre, Mario; Pulido, Gregorio Toscano; Coello, Carlos A. Coello
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28 Citations
An important issue with Evolutionary Algorithms (EAs) is the way to identify the best solutions in order to guide the search process. Fitness comparisons among solutions in singleobjective optimization is straightforward, but when dealing with multiple objectives, it becomes a nontrivial task. Pareto dominance has been the most commonly adopted relation to compare solutions in a multiobjective optimization context. However, it has been shown that as the number of objectives increases, the convergence ability of approaches based on Pareto dominance decreases. In this paper, we propose three novel fitness assignment methods for manyobjective optimization. We also perform a comparative study in order to investigate how effective are the proposed approaches to guide the search in highdimensional objective spaces. Results indicate that our approaches behave better than six stateoftheart fitness assignment methods.
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Mendoza, Sonia; Decouchant, Dominique; Morán, Alberto L.; Enríquez, Ana María Martínez; Favela, Jesus
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In order to facilitate and improve collaboration among coauthors, working in the Web environment, documents must be made seamlessly available to them. Web documents may contain multimedia resources, whose management raises important issues due to the constraints and limits imposed by Web technology. This paper proposes an adaptive support for distributing shared Web documents and multimedia resources across authoring group sites. Our goal is to provide an efficient use of costly Web resources. Distribution is based on the current arrangement of the participating sites, the roles granted to the coauthors and the site capabilities. We formalize key concepts to ensure that system’s properties are fulfilled under the specified conditions and to characterize distribution at a given moment. The proposed support has been integrated into the PIÑAS platform, which allows an authoring group to collaboratively and consistently produce shared Web documents.
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NavaOrtiz, M.; GómezFlores, W.; DíazPérez, A.; ToscanoPulido, G.
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Segmentation is an important step within optical character recognition systems, since the recognition rates depends strongly on the accuracy of binarization techniques. Hence, it is necessary to evaluate different segmentation methods for selecting the most adequate for a specific application. However, when gold patterns are not available for comparing the binarized outputs, the recognition rates of the entire system could be used for assessing the performance. In this article we present the evaluation of five local adaptive binarization methods for digit recognition in water meters by measuring misclassification rates. These methods were studied due to of their simplicity to be implemented in basedcamera devices, such as cell phones, with limited hardware capabilities. The obtained results pointed out that Bernsens method achieved the best recognition rates when the normalized central moments are employed as features.
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Trautmann, Heike; Rudolph, Günter; DominguezMedina, Christian; Schütze, Oliver
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9 Citations
The averaged Hausdorff distance Δ_{p} is a performance indicator in multiobjective evolutionary optimization which simultaneously takes into account proximity to the true Pareto front and uniform spread of solutions. Recently, the multiobjective evolutionary algorithm Δ_{p}EMOA was introduced which successfully generates evenly spaced Pareto front approximations for biobjective problems by integrating an external archiving strategy into the SMSEMOA based on Δ_{p}. In this work a conceptual generalization of the Δ_{p}EMOA for higher objective space dimensions is presented and experimentally compared to stateofthe art EMOA as well as specialized EMOA variants on threedimensional optimization problems.
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Korzhik, Valery; MoralesLuna, Guillermo
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1 Citations
We consider a cryptographic scenario where some center broadcasts a random binary string to Alice, Bob and Eve over binary symmetric channels with bit error probabilities ε_{A}, ε_{B} and ε_{E} respectively. Alice and Bob share no secret key initially, and their goal is to generate, after public discussion, a common informationtheoretically secure key facing an active eavesdropper Eve. Under the condition ε_{A}<ε_{E} and ε_{B}<ε_{E}, code authentication (CA) can be used as part of a public discussion protocol to solve this problem. This authentication exploits parts of substrings received by Alice and Bob from the broadcasting center as authenticators to messages transmitted in a public discussion. Unfortunately, it happens to be ineffective because it produces a key of small length. We propose a hybrid authentication (HA) that combines both keyless code authentication and key authentication based on an almost strong universal class of hash functions. We prove a theorem that allows estimation of the performance evaluation of hybrid authentication. The selection algorithm for the main HA parameters, given security and reliability thresholds, is presented in detail.
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Tanveer, Saad; Muhammad, Aslam; MartinezEnriquez, A. M.; EscaladaImaz, G.
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Languages like Spanish and Arabic are spoken over a large geographic area. The people that speak these languages develop differences in accent, annotation and phonetic delivery. This leads to difficulty in standardization of languages for education and communication (both text and oral). The problem is addressed by phonetic dictionaries to some extent. They provide the correct pronunciation for a word. But, they contribute little to standardize or unify the language for a learner. Our system is to provide unification of different accents and dialects. It creates a standard for learning and communication.
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Decouchant, Dominique; MartńezEnríquez, Ana Mará; Favela, Jesús; L.Morán, Alberto; Mendoza, Sonia; Jafar, Samir
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1 Citations
This paper is directly focused on the design of middleware functions to support a distributed cooperative authoring environment on the World Wide Web. Using the advanced storage and access functions of the PIÑAS middleware, coauthors can produce fragmented and replicated documents in a structured, consistent and efficient way. However, despite it provides elaborated, concerted, secure and parameterizable cooperative editing support and mechanisms, this kind of applications requires a suited and efficient interapplication communication service to design and implement flexible, efficient, and adapted group awareness functionalities.
Thus, we developed a proofofconcept implementation of a centralized version of a Distributed Event Management Service that allows to establish communication between cooperative applications, either in distributed or centralized mode. As an essential component for the development of cooperative environments, this Distributed Event Management Service allowed us to design an Adaptive Group Awareness Engine whose aim is to automatically deduce and adapt coauthor’s cooperative environments to allow them collaborate closer. Thus, this user associated inference engine captures the application events corresponding to author’s actions,and uses its knowledge and rule bases,to detect coauthor’s complementary or related work, specialists, or beginners, etc. Its final goal is to propose modifications to the author working environments, application interfaces, communication or interaction ways, etc.
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Flores, Juan J.; López, Rodrigo; Barrera, Julio
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4 Citations
Evolutionary computation is inspired by nature in order to formulate metaheuristics capable to optimize several kinds of problems. A family of algorithms has emerged based on this idea; e.g. genetic algorithms, evolutionary strategies, particle swarm optimization (PSO), ant colony optimization (ACO), etc. In this paper we show a populationbased metaheuristic inspired on the gravitational forces produced by the interaction of the masses of a set of bodies. We explored the physics knowledge in order to find useful analogies to design an optimization metaheuristic. The proposed algorithm is capable to find the optima of unimodal and multimodal functions commonly used to benchmark evolutionary algorithms. We show that the proposed algorithm (Gravitational Interactions Optimization  GIO) works and outperforms PSO with niches in both cases. Our algorithm does not depend on a radius parameter and does not need to use niches to solve multimodal problems. We compare GIO with other metaheuristics with respect to the mean number of evaluations needed to find the optima.
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Gómez, Victor; Mendoza, Sonia; Decouchant, Dominique; Rodríguez, José
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Ubiquitous computing integrates Internet/Intranet small integrated sensors as well as powerful and dynamic devices into the people’s working and domestic areas. An intelligent area contains many devices that provide information about the state of each artifact (e.g., power failure of the refrigerator) without user intervention. Service discovery systems are essential to achieve this sophistication as they allow services and users to discover, configure and communicate with other services and users. However, most of these systems only provide support for interaction between services and software clients. In order to cope with this limitation, the SEDINU system aims at supporting interactions between nomadic users and services provided by areas. As users may move within the organization from an area to another one in order to accomplish their tasks, this system also provides support for useruser interaction and collaboration under specific contexts (role, location and goals).
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Guerrero Huerta, Ana Georgina; Hernández Rubio, Erika; Meneses Viveros, Amilcar
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Specialists in the area of mental health require tools that allow them to apply their tests to elderly patients more efficiently and do not lose effectiveness. One of these tests is the Yerkes test. On the one hand, implementing this test requires that it be like an augmented reality application. On the other hand, it is known that tablets are ideal are suitable devices to develop applications aimed at older adults. This paper presents the design of a prototype of the Yerkes test in augmented reality tablets, aimed to older adults.
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Trujillo, Leonardo; ZFlores, Emigdio; JuárezSmith, Perla S.; Legrand, Pierrick; Silva, Sara; Castelli, Mauro; Vanneschi, Leonardo; Schütze, Oliver; Muñoz, Luis
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There are two important limitations of standard treebased genetic programming (GP). First, GP tends to evolve unnecessarily large programs, what is referred to as bloat. Second, GP uses inefficient search operators that focus on modifying program syntax. The first problem has been studied extensively, with many works proposing bloat control methods. Regarding the second problem, one approach is to use alternative search operators, for instance geometric semantic operators, to improve convergence. In this work, our goal is to experimentally show that both problems can be effectively addressed by incorporating a local search optimizer as an additional search operator. Using realworld problems, we show that this rather simple strategy can improve the convergence and performance of treebased GP, while also reducing program size. Given these results, a question arises: Why are local search strategies so uncommon in GP? A small survey of popular GP libraries suggests to us that local search is underused in GP systems. We conclude by outlining plausible answers for this question and highlighting future work.
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VázquezSantacruz, Eduardo; Chakraborty, Debrup
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In this paper we present a new method to create neural network ensembles. In an ensemble method like bagging one needs to train multiple neural networks to create the ensemble. Here we present a scheme to generate different copies of a network from one trained network, and use those copies to create the ensemble. The copies are produced by adding controlled noise to a trained base network. We provide a preliminary theoretical justification for our method and experimentally validate the method on several standard data sets. Our method can improve the accuracy of a base network and give rise to considerable savings in training time compared to bagging.
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García, Edscott Wilson; MoralesLuna, Guillermo
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In the case of desktop grids, a single hardwaredetermined latency and constant bandwidth between processors cannot be assumed without incurring in unnecessary error. The actual network topology is determined not only by the physical hardware, but also by the instantaneous bandwidth availability for parallel processes to communicate. In this paper we present a novel task assignment scheme which takes the dynamic network topology into consideration along with the traditionally evaluated variables such as processor availability and potential. The method performs increasingly better as the grid size increases.
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García, Kimberly; KirschPinheiro, Manuele; Mendoza, Sonia; Decouchant, Dominique
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1 Citations
Most of the working environments offer multiple hardware and software that could be shared among the members of staff. However, it could be particularly difficult to take advantages of all these resources without a proper software support capable of discovering the ones that fulfill both a user’s requirements and each resource owner’s sharing preferences. To try to overcome this problem, several service discovery protocols have been developed, aiming to promote the use of network resources and to reduce configuration tasks. Unfortunately, these protocols are mainly focused on finding resources based just on their type or some minimal features, lacking information about: user preferences, restrictions and contextual variables. To outstrip this deficiency, we propose to exploit the power of semantic description, by creating a knowledge base integrated by a set of ontologies generically designed to be adopted by any type of organization. To validate this proposal, we have customized the ontologies for our case of study, which is a research center.
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Korzhik, Valery; Imai, Hideki; Shikata, Junji; MoralesLuna, Guillermo; Gerling, Ekaterina
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4 Citations
It is very common to use the notion of relative entropy (or KullbackLeibler divergence) as a measure for the discrimination difficulty among the hypotheses testing of presence and absence within a steganographic system. Relative entropy is not a symmetric function and sometimes it is very hard to compute its values. We propose to customize the notion of Bhattacharyya distance to the solution of the same problem. The main properties of Bhattacharyya distance are presented. We show applications of this new steganographic system security criterion within the model with a Gaussian colored covertext and within spreadspectrum watermarking by a white Gaussian sequence.
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Sato, Hiroyuki; Coello Coello, Carlos A.; Aguirre, Hernán E.; Tanaka, Kiyoshi
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To realize effective genetic operation in evolutionary manyobjective optimization, crossover controlling the number of crossed genes (CCG) has been proposed. CCG controls the number of crossed genes by using an userdefined parameter α. CCG with small α significantly improves the search performance of multiobjective evolutionary algorithm in manyobjective optimization by keeping small the number of crossed genes. However, to achieve high search performance by using CCG, we have to find out an appropriate parameter α by conducting many experiments. To avoid parameter tuning and automatically find out an appropriate α in a single run of the algorithm, in this work we propose an adaptive CCG which adopts the parameter α during the solutions search. Simulation results show that the values of α controlled by the proposed method converges to an appropriate value even when the adaptation is started from any initial values. Also we show the adaptive CCG achieves more than 80% with a single run of the algorithm for the maximum search performance of the static CCG using an optimal α^{*}.
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MartínezAngeles, Carlos Alberto; Dutra, Inês; Costa, Vítor Santos; BuenabadChávez, Jorge
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3 Citations
We present the design and evaluation of a Datalog engine for execution in Graphics Processing Units (GPUs). The engine evaluates recursive and nonrecursive Datalog queries using a bottomup approach based on typical relational operators. It includes a memory management scheme that automatically swaps data between memory in the host platform (a multicore) and memory in the GPU in order to reduce the number of memory transfers. To evaluate the performance of the engine, four Datalog queries were run on the engine and on a single CPU in the multicore host. One query runs up to 200 times faster on the (GPU) engine than on the CPU.
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MartínezEnríquez, Ana María; Muhammad, Aslam; Decouchant, Dominique; Favela, Jeséus
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2 Citations
This paper describes the principle of an inference engine that analyzes useful information of actions, performed by cooperating users, to propose modifications of the states and/or the presentation of the shared objects. Using cooperative groupware applications, a group of people may work on the same task while other users may pursue their individual goals using various other applications (cooperative or noncooperative)with different roles. In such environment, consistency, group awareness and security have essential signifficance. The work of each user can be observed by capturing their actions and then analyzing them in relation to the history of previous actions. The proposed Adaptive Inference Engine (AIE)behaves as a consumer of application events which analyzes this information on the basis of some predefined rules and then proposes some actions that may be applied within the cooperative environment. In all cases, the user controls the execution of the proposed group awareness actions in his working environment. A prototype of the AIE is developed using the Amaya Web Authoring Toolkit and the PI ~NAS collaborative authoring middleware.
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Korzhik, Valery; MoralesLuna, Guillermo; Lee, Moon Ho
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6 Citations
There are several steganography techniques (e.g. linguistic or least significant bit embedding) that provide security but no robustness against an active adversary. On the other hand it is rather well known that the spreadspectrum based technique is robust against an active adversary but it seems to be insecure against a statistical detection of stegosignal. We prove in this paper that actually this is not the case and that there exists an stegosystem that is asymptotically both secure to statistical detection and robust against a jamming of stegosignal by an active adversary. We call such stegosystems quasiperfect whereas we call them perfect if in addition the data rate of secret information is asymptotically constant. We prove that perfect stegosystems do not exist for both blind and informed decoders. Some examples using the simplex and the ReedMuller codes jointly with stegosystems are given.
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MoralesLuna, Guillermo
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#kSAT is a complex problem equivalent to calculate the cardinalities of the null sets of conjunctive forms consisting of clauses with an uniform length. Each such null set is the union of linear varieties of uniform dimension in the hypercube. Here we study the class of sets in the hypercube that can be realized as such null sets. We look toward to characterize their cardinalities and the number of ways that they can be expressed as unions of linear varieties of uniform dimension. Using combinatorial and graph theory argumentations, we give such characterizations for very extremal values of k, either when it is very small or close to the hypercube dimension, and of the number of clauses appearing in an instance, either of value 2, or big enough to get a contradiction.
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MartínezAngeles, Carlos Alberto; Dutra, Inês; Costa, Vítor Santos; BuenabadChávez, Jorge
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Markov Logic is an expressive and widely used knowledge representation formalism that combines logic and probabilities, providing a powerful framework for inference and learning tasks. Most Markov Logic implementations perform inference by transforming the logic representation into a set of weighted propositional formulae that encode a Markov network, the ground Markov network. Probabilistic inference is then performed over the grounded network.
Constructing, simplifying, and evaluating the network are the main steps of the inference phase. As the size of a Markov network can grow rather quickly, Markov Logic Network (MLN) inference can become very expensive, motivating a rich vein of research on the optimization of MLN performance. We claim that parallelism can have a large role on this task. Namely, we demonstrate that widely available Graphics Processing Units (GPUs) can be used to improve the performance of a stateoftheart MLN system, Tuffy, with minimal changes. Indeed, comparing the performance of our GPUbased system, TuGPU, to that of the Alchemy, Tuffy and RockIt systems on three widely used applications shows that TuGPU is up to 15x times faster than the other systems.
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Toxqui, Rigoberto Toxqui; Yu, Wen; Li, Xiaoou
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2 Citations
This paper considers the problem of PD control of overhead crane in the presence of uncertainty associated with crane dynamics. By using radial basis function neural networks, these uncertainties can be compensated effectively. This new neural control can resolve the two problems for overhead crane control: 1) decrease steadystate error of normal PD control. 2) guarantee stability via neural compensation. By Lyapunov method and inputtostate stability technique, we prove that these robust controllers with neural compensators are stable. Realtime experiments are presented to show the applicability of the approach presented in this paper.
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Li, Xiaoou; Medina Marń, Joselito; Chapa, Sergio V.
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1 Citations
Active database systems have been developed for applications needing an automatic reaction in response to certain conditions being satisfied or certain event occurring. The desired behavior is expressed by ECArules (eventconditionaction rules). Generally, ECA rules and their execution are represented by rule language, for example, defining TRIGGERs in an active database. Then, database behavior prediction or analysis can be realized through other approaches such as algebraic approach, trigger graph methods, etc.. Therefore, in such active databases, rule representation and processing are separated. In this paper we propose a structural model which integrates rule representation and processing entirely, it is called Conditional Colored Petri Net (CCPN). CCPN can model both rules themselves and their complicated interacting relation in an graphical way. If the rule base of an active database is modeled by CCPN, then rule simulation can be done. An example is illustrated in the paper.
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CruzCortés, Nareli; TrejoPérez, Daniel; Coello, Carlos A. Coello
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13 Citations
In this paper, we present a study of the use of an artificial immune system (CLONALG) for solving constrained global optimization problems. As part of this study, we evaluate the performance of the algorithm both with binary encoding and with realnumbers encoding. Additionally, we also evaluate the impact of the mutation operator in the performance of the approach by comparing Cauchy and Gaussian mutations. Finally, we propose a new mutation operator which significantly improves the performance of CLONALG in constrained optimization.
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Lara, Adriana; Alvarado, Sergio; Salomon, Shaul; Avigad, Gideon; Coello Coello, Carlos A.; Schütze, Oliver
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4 Citations
Recently, the Directed Search Method has been proposed as a pointwise iterative search procedure that allows to steer the search, in any direction given in objective space, of a multiobjective optimization problem. While the original version requires the objectives’ gradients, we consider here a possible modification that allows to realize the method without gradient information. This makes the novel algorithm in particular interesting for hybridization with set oriented search procedures, such as multiobjective evolutionary algorithms.
In this paper, we propose the DDS, a gradient free Directed Search method, and make a first attempt to demonstrate its benefit, as a local search procedure within a memetic strategy, by integrating the DDS into the wellknown algorithmMOEA/D. Numerical results on some benchmark models indicate the advantage of the resulting hybrid.
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Decouchant, Dominique; Mendoza, Sonia; Rodríguez, José
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Researches and efforts currently being developed within the World Wide Web environment, whose aim is to provide cooperative supports, are mainly performed in the field of the “Semantic Web”. These efforts are based on technological components such as the XML, RDF, and OWL languages that allow the cooperative definition of distributed ontologies. From these components, it is possible to develop “reasoning” programs that are able a) to infer information from data described with these languages and b) to exploit the defined ontologies. Moreover, programs may also be defined to provide supports to collaborators to cooperatively exploit the defined ontologies. However, all theses efforts remain developed at the application level. Thus, no suited distributed support for Web cooperative work had been investigated that deals with the unreliability of such a distributed environment.
In this chapter, we present the PIÑAS infrastructure which provides means for supporting cooperative work on the Web. Using cooperative applications that are built employing the services of this infrastructure, several users can access and modify replicated shared entities in a consistent and controlled way. PIÑAS provides suited features, such as: user identification, multisite user definition, user and entity naming, shared entity fragmentation and replication, storage, consistency, and automatic distributed updating. We propose seamless extensions to standard Web services that can be fully integrated within the Web environment. Moreover, the innovative PIÑAS features provide reliable support for temporarily disconnected and nomadic work.
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Coello Coello, Carlos A.; Becerra, Ricardo Landa
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2 Citations
In this paper, we propose a technique that exploits knowledge extracted during the search to improve the performance of an evolutionary algorithm used for global optimization. The approach is based on a cultural algorithm combined with evolutionary programming and we show that produces highly competitive results at a relatively low computational cost.
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Farzana, J.; Muhammad, Aslam; MartinezEnriquez, A. M.; Afraz, Z. S.; Talha, W.
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Vision loss is one of ultimate obstacle in the lives of blind that prevent them to perform tasks on their own and selfreliantly. The blind are trusting on others for the selection of trendy and eyecatching accessories because self –buying effort lead them in such collection that is mismatch with their personalities and society style. That is why they are bound to depend upon on their family for shopping assistance, who often may not afford quality time due to busy routine. The thought of dependency rises lack of selfconfidence in blinds, absorbs their ability to negotiate, decision making power, and social activities. Via uninterrupted speech communication, our proposed talking accessories selector assistant for the blind provides quick decision support in picking the routinely wearable accessories like dress, shoes, cosmetics, according to the society drifts and events. The foremost determination of this assistance is to make the blind liberated and more assertive.
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SánchezAdame, Luis Martín; Mendoza, Sonia; GonzálezBeltrán, Beatriz A.; Meneses Viveros, Amilcar; Rodríguez, José
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A virtual community is a social group of any size that shares common interests and communicates through the Internet. A user joins a virtual community not only because of its popularity or the quality of its contents, but also owing to the user experience that the platform offers. Anticipated User eXperience (AUX) allows knowing the idealisations, hopes, and desires of the users in a very early stage of any development. Participation is a crucial component in the growth and survival of any virtual community. An essential element for people to participate in a virtual community is that the platform should provide suitable user tools, which are widgets that allow users to interact with their peers. We propose an AUX evaluation framework for user tools, whose intention is to improve their design, and through it, the participation of users.
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Korjik, Valeri; MoralesLuna, Guillermo; Balakirsky, Vladimir B.
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3 Citations
Secret key agreement protocol between legal parties based on reconciliation and privacy amplification procedure has been considered in [2]. The so called privacy amplification theorem is used to estimate the amount of Shannon’s information leaking to an illegal party (passive eavesdropper) about the final key.We consider a particular case where one of the legal parties (Alice) sends to another legal party (Bob) a random binary string x through a binary symmetric channel (BSC) with bit error probability ε_{m} while an eavesdropper (Eve) receives this string through an independent BSC with bit error probability ε_{w}. We assume that ε_{m} < ε_{w} and hence the main channel is superior to the wiretap channel. To reconcile the strings between legal parties Alice sends to Bob through noiseless channel the check string y based on some good error correcting code. Since this transmission is completely public Eve can eavesdrop it and therefore this extra information has to be taken into account in an estimation of the information leaking to Eve about the final key. In [3] an inequality has been proved to upper bound the information of Eve in such scenario. The main contribution of the running paper is to improve this inequality and hence to enhance the privacy amplification theorem. We present also bounds for the probability of false reconciliation when the check symbols of the linear code are transmitted through noiseless channel. The presented results can be very useful when considering the nonasymptotic case.
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Jesús Rubio, José; Yu, Wen
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In this paper, we present a new sliding mode controller for a class of unknown nonlinear discretetime systems. We make the following two modifications: 1) The neural identifier which is used to estimate the unknown nonlinear system, applies new learning algorithms. The stability and nonzero properties are proved by deadzone and projection technique. 2) We propose a new sliding surface and give a necessary condition to assure exponential decrease of the sliding surface. The timevarying gain in the sliding mode produces a lowchattering control signal. The closedloop system with sliding mode controller and neural identifier is proved to be stable by Lyapunov method.
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Li, Xiaoou; Yu, Wen
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By using differential neural networks, we present a novel robust adaptive controller for a class of unknown nonlinear systems. First, deadzone and projection techniques are applied to neural model, such that the identification error is bounded and the weights are different from zero. Then, a linearization controller is designed based on the neuro identifier. Since the approximation capability of the neural networks is limited, four kinds of compensators are addressed.
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HernándezRubio, Erika; MenesesViveros, Amilcar; ManceraSerralde, Erick; FloresOrtiz, Javier
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Mnesic problems in older adults is a global health problem. Some proposals have been made to support health care in older adults using mobile technologies. In particular,there are analysis and design of mobile applications focusing on the elderly to apply memory tests Luria. For example, in word learning test, multiple words or numerical figures unraleted are shown to the patient. The number of item exceed the numer that the patient can remember. Usually the serie consist of ten or twelve words or numerical digits. After this task, the patient is asked to repeat the series in any order. In one hand, the physical deterioration of the elderly makes it difficult the usability of the user interface of mobile applications. These deteriorations can be auditory, visual and motor. They are particular to each elderly. For this reason, a traditional user interface loses effectiveness when it has interaction with older people. In another hand, some studies suggest that Tablets are the best mobile devices for older adults, because the size of their screen and usability of their user interface. However, tablets have different modes of interaction and it is not yet clear how the elderly respond to them. One solution to this problem is to provide different modalities for interaction. This modalities they must be presents in applications for tablets. In this work, we present the implementation of the test world learning Luria memory test. And we implemented several combinations of modalities for the test. Finally we present the result of interaction with the older adults.
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Coello Coello, Carlos A.; Pulido, Gregorio
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89 Citations
In this paper, we propose a multiobjective optimization approach based on a micro genetic algorithm (microGA) which is a genetic algorithm with a very small population (four individuals were used in our experiment) and a reinitialization process. We use three forms of elitism and a memory to generate the initial population of the microGA. Our approach is tested with several standard functions found in the specialized literature. The results obtained are very encouraging, since they show that this simple approach can produce an important portion of the Pareto front at a very low computational cost.
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Gómez, Juan Carlos; Hernández, Fernando; Coello, Carlos A. Coello; Ronquillo, Guillermo; Trejo, Antonio
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This paper introduces a Genetic Algorithm (GA) for training Artificial Neural Networks (ANNs) using the electromagnetic spectrum signal of a combustion process for flame pattern classification. Combustion requires identification systems that provide information about the state of the process in order to make combustion more efficient and clean. Combustion is complex to model using conventional deterministic methods thus motivate the use of heuristics in this domain. ANNs have been successfully applied to combustion classification systems; however, traditional ANN training methods get often trapped in local minima of the error function and are inefficient in multimodal and nondifferentiable functions. A GA is used here to overcome these problems. The proposed GA finds the weights of an ANN than best fits the training pattern with the highest classification rate.
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Yu, Wen; Li, Xiaoou
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In general, RBF neural network cannot match nonlinear systems exactly. Unmodeled dynamic leads parameters drift and even instability problem. According to system identification theory, robust modification terms must be included in order to guarantee Lyapunov stability. This paper suggests new learning laws for normal and adjustable RBF neural networks based on InputtoState Stability (ISS) approach. The new learning schemes employ a timevarying learning rate that is determined from inputoutput data and model structure. The calculation of the learning rate does not need any prior information such as estimation of the modeling error bounds.
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Chakraborty, Debrup
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In this work we propose a new method to create neural network ensembles. Our methodology develops over the conventional technique of bagging, where multiple classifiers are trained using a single training data set by generating multiple bootstrap samples from the training data. We propose a new method of sampling using the knearest neighbor density estimates. Our sampling technique gives rise to more variability in the data sets than by bagging. We validate our method by testing on several real data sets and show that our method outperforms bagging.
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Sandoval, Alejandro Cruz; Yu, Wen; Li, Xiaoou
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Many physical systems contains fast and slow phenomenons. In this paper we propose a dynamic neural networks with different timescales to model the nonlinear system. Passivitybased approach is used to derive stability conditions for neural identifer. Several stability properties, such as passivity, asymptotic stability, inputtostate stability and bounded input bounded output stability, are guaranteed in certain senses. Numerical examples are also given to demonstrate the effectiveness of the theoretical results.
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Muhammad, Aslam; Enríquez, Ana María Martínez; Decouchant, Dominique
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This paper presents our approach to design and provide elaborated awareness coordination functions for cooperative production of complex Web shared documents. We designed a Group Awareness Inference Engine (GAIE) that catches working focus of collaborators and then deduces some of their potential interests for communication to enhance coordination and cooperative production.
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AlvarezGallegos, Jaime; Villar, Carlos Alberto Cruz; Flores, Edgar Alfredo Portilla
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4 Citations
This paper presents a dynamic optimization approach based on the differential evolution (DE) strategy which is applied to the concurrent optimal design of a continuously variable transmission (CVT). The structurecontrol integration approach is used to state the concurrent optimal design as a dynamic optimization problem which is solved using the Constraint Handling Differential Evolution (CHDE) algorithm. The DE strategy is compared with the sequential approach. The results presented here demonstrate that the DE strategy is less expensive than the sequential approach from the computational implementation point of view.
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Rudolph, Günter; Trautmann, Heike; Sengupta, Soumyadip; Schütze, Oliver
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9 Citations
In some technical applications like multiobjective online control an evenly spaced approximation of the Pareto front is desired. Since standard evolutionary multiobjective optimization (EMO) algorithms have not been designed for that kind of approximation we propose an archivebased plugin method that builds an evenly spaced approximation using averaged Hausdorff measure between archive and reference front. In case of three objectives this reference font is constructed from a triangulated approximation of the Pareto front from a previous experiment. The plugin can be deployed in online or offline mode for any kind of EMO algorithm.
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Cruz Caballero, Pedro; MenesesViveros, Amilcar; HernándezRubio, Erika; Zamora Arévalo, Oscar
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Poppelreuter and Raven tests are used by psychologists to analyze cognitive abilities, mental diseases like visual agnosia, and even dementia syndromes like Alzheimer. It is known that this tests can be applied using mobile devices. However, the natural deterioration of the elderly, particularly visual weakness, may cause problems when using devices, even with Large or Xlarge screens. In order to reduce this problems, we proposed the use of a Distributed User Interface, using a tablet and an smartTV, to support users with visual problems to do Poppelreuter and Raven tests. At the end of our research we confirm that the application of visual tests using a Distributed User Interface is feasible.
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Zulfiqar, Ali; Muhammad, Aslam; MartinezEnriquez, Ana Maria; EscaladaImaz, G.
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Every feature extraction and modeling technique of voice/speech is not suitable in all type of environments. In many real life applications, it is not possible to use all type of feature extraction and modeling techniques to design a single classifier for speaker identification tasks because it will make the system complex. So instead of exploring more techniques or making the system complex it is more reasonable to develop the classifier by using existing techniques and then combine them by using different combination techniques to enhance the performance of the system. Thus, this paper describes the design and implementation of a VQHMM based Multiple Classifier System by using different combination techniques. The results show that the developed system by using confusion matrix significantly improve the identification rate.
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Cruz Caballero, Pedro; Viveros, Amilcar Meneses; HernándezRubio, Erika
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Luria’s tests can be used, mainly by psychologists, neuropsychologists or any other mental specialist, to analyze mental decline in older adults. The application of Luria’s tests in older adults using mobile devices may encounter different obstacles, not only because of visual, cognitive, and physical limitations but also when using devices with limited screen attributes or touch space. One of the most typical solution includes the implementation of contextual plasticity, which provide the applications with the possibility of use the best interface modality based on the user’s capabilities or to take advantage of closer devices like secondary screens. In this work we present a distributed graphic user interface for three Luria’s visual perceptual tests for older adults. This distributed graphic user interface is implemented in a prototype for iOS, using iPad and appleTV.
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