New results on the genetic cryptanalysis of TEA and reduced-round versions of XTEA

Congress on Evolutionary Computation. Portland, USA, 19-23 June 2004Recently, a simple way of creating very efficient distinguishers for cryptographic primitives such as block ciphers or hash functions, was presented by the authors. Here, this cryptanalysis attack is shown to be successful when applied over reduced round versions of the block cipher XTEA. Additionally, a variant of this genetic attack is introduced and its results over TEA shown to be the most powerful published to date

Finding efficient nonlinear functions by means of genetic programming

7th International Conference, KES 2003. Proceedings, Part I. Oxford, UK, September 3-5, 2003The design of highly nonlinear functions is relevant for a number of different applications, ranging from database hashing to message authentication. But, apart from useful, it is quite a challenging task. In this work, we propose the use of genetic programming for finding functions that optimize a particular nonlinear criteria, the avalanche effect, using only very efficient operations, so that the resulting functions are extremely efficient both in hardware and in software.Supported by the Spanish Ministerio de Ciencia y Tecnologia research project TIC2002-04498-C05-4Publicad

On the design of state-of-the-art pseudorandom number generators by means of genetic programming

Congress on Evolutionary Computation. Portland, EEUU, 19-23 June 2004The design of pseudorandom number generators by means of evolutionary computation is a classical problem. Today, it has been mostly and better accomplished by means of cellular automata and not many proposals, inside or outside this paradigm could claim to be both robust (passing all the statistical tests, including the most demanding ones) and fast, as is the case of the proposal we present here. Furthermore, for obtaining these generators, we use a radical approach, where our fitness function is not at all based in any measure of randomness, as is frequently the case in the literature, but of nonlinearity. Efficiency is assured by using only very efficient operators (both in hardware and software) and by limiting the number of terminals in the genetic programming implementation

Evolving hash functions by means of genetic programming

Proceedings of the 8th annual conference on Genetic and evolutionary computation. Seattle, Washington, USA, July 08-12, 2006The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fast hash functions. We use a fitness function based on a non-linearity measure, producing evolved hashes with a good degree of Avalanche Effect. Efficiency is assured by using only very fast operators (both in hardware and software) and by limiting the number of nodes. Using this approach, we have created a new hash function, which we call gp-hash, that is able to outperform a set of five human-generated, widely-used hash functions.This article has been financed by the Spanish founded research MCyT project OP:LINK, Ref:TIN2005-08818-C04-02.Publicad

Finding state-of-the-art non-cryptographic hashes with genetic programming

Proceding of: 9th International Conference, Reykjavik, Iceland, September 9-13, 2006.The design of non-cryptographic hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this paper, we use the Genetic Programming paradigm to evolve collision free and fast hash functions. For achieving robustness against collision we use a fitness function based on a non-linearity concept, producing evolved hashes with a good degree of Avalanche Effect. The other main issue, efficiency, is assured by using only very fast operators (both in hardware and software) and by limiting the number of nodes. Using this approach, we have created a new hash function, which we call gp-hash, that is able to outperform a set of five human-generated, widely-used hash functions.This article has been financed by the Spanish founded research MCyT project OP:LINK, Ref:TIN2005-08818-C04-02

Finding Efficient Distinguishers for Cryptographic Mappings, with an Application to the Block Cipher TEA

A simple way of creating new and very efficient distinguishers for cryptographic primitives, such as block ciphers or hash functions, is introduced. This technique is then successfully applied over reduced round versions of the block cipher TEA, which is proven to be weak with less than five cycles.This researchwas supported by project TIC2002-04498- C05-4 of the Spanish Ministerio de Ciencia y Tecnologia.Publicad

Using classifiers to predict linear feedback shift registers

Proceeding of: IEEE 35th International Carnahan Conference on Security Technology. October 16-19, 2001, LondonPreviously (J.C. Hernandez et al., 2000), some new ideas that justify the use of artificial intelligence techniques in cryptanalysis are presented. The main objective of that paper was to show that the theoretical next bit prediction problem can be transformed into a classification problem, and this classification problem could be solved with the aid of some AI algorithms. In particular, they showed how a well-known classifier called c4.5 could predict the next bit generated by a linear feedback shift register (LFSR, a widely used model of pseudorandom number generator) very efficiently and, most importantly, without any previous knowledge over the model used. The authors look for other classifiers, apart from c4.5, that could be useful in the prediction of LFSRs. We conclude that the selection of c4.5 by Hernandez et al. was adequate, because it shows the best accuracy of all the classifiers tested. However, we have found other classifiers that produce interesting results, and we suggest that these algorithms must be taken into account in the future when trying to predict more complex LFSR-based models. Finally, we show some other properties that make the c4.5 algorithm the best choice for this particular cryptanalytic problem.Publicad

How to distinguish between a block cipher and a random permutation by lowering the input entropy

IEEE 35th International Carnahan Conference on Security Technology. Londres, 16-19 October 2001A novel cryptanalysis technique is presented, and its suitability for distinguishing a block cipher algorithm or a hash function from a random permutation is explained. Additionally, we propose a genetic algorithm based implementation and show some preliminary results of these ideas on reduced rounds versions of the block cipher TEA

Distribución de cargas en una esfera mediante estrategias evolutivas

En este trabajo se plantea la resolución mediante estrategias evolutivas de un problema clásico de la física, el problema de Thomson, consistente en distribuir n cargas iguales en la superficie de una esfera o, lo que es lo mismo, hallar la distribución que hace mínimo el potencial electrostático de las cargas. La dificultad de hallar este mínimo radica en el hecho de que el número de las disposiciones estables aumentan exponencialmente con el número de cargas. Hasta la fecha aún no existe una función que relacione de forma exacta el potencial mínimo con el número de cargas, si bien se han propuesto aproximaciones asintóticas para dicha función. El objetivo de este trabajo es encontrar un algoritmo que evite estas dificultades y permita calcular configuraciones para más cargas con menor coste computacional. Como resultado se obtiene un método que mejora los estándares dentro de las estrategias evolutivas.Publicad