Cryptanalysis of an EPC Class-1 Generation-2 Standard Compliant Authentication Protocol

It is hard for the cryptanalysts to apply traditional techniques and brute-force attacks against feistel ciphers due to their inherent structure based on high nonlinearity and low autocorrelation. In this paper, we propose a technique for the cryptanalysis of four-rounded Data Encryption Standard (DES) based on Binary Ant Colony Optimization (BACO). A known plaintext attack is used to recover the secret key of the DES cipher. The environment for the ants is a directed graph, which we call search space, is constructed for efficiently searching the secret key. We also develop a heuristic function which measures the quality of a constructed solution. Several optimum keys are computed over different runs on the basis of routes completed by the ants. These optimum keys are then used to find each individual bit of the 56 bit secret key used by DES. The results of our experiments show that ACO is an effective technique for the cryptanalysis of four-rounded DES. To the best of our knowledge, this is the first time that BACO has been used for this specific problem.

Cryptanalysis of Four-Rounded DES Using Ant Colony Optimization

Cryptanalysis of feistel ciphers is difficult due to their high nonlinearity and autocorrelation. On the other hand, substitution ciphers are easily breakable due to their simpler encryption process. In this paper, a highly efficient Binary Particle Swarm Optimization (PSO) based cryptanalysis approach for four-rounded Data Encryption Standard (DES) is presented. Several optimum keys are generated in different runs of the algorithm on the basis of their fitness value and finally, the real key is found by guessing every individual bit. The robustness of the proposed technique is also checked for eight-rounded DES. Our approach shows promising results when compared with the cryptanalysis of DES performed by other techniques such as Genetic Algorithm (GA).

Cryptanalysis of four-rounded DES using binary particle swarm optimization

The Tiny Encryption Algorithm (TEA) is a Feistel block cipher well known for its simple implementation, small memory footprint, and fast execution speed. In two previous studies, genetic algorithms (GAs) were employed to investigate the randomness of TEA output, based on which distinguishers for TEA could be designed. In this study, we used quan-tum-inspired genetic algorithms (QGAs) in the cryptanalysis of TEA. Quantum chromosomes in QGAs have the advan-tage of containing more information than the binary counterpart of the same length in GAs, and therefore generate a more diverse solution pool. We showed that QGAs could discover distinguishers for reduced cycle TEA that are more efficient than those found by classical GAs in two earlier studies. Furthermore, we applied QGAs to break four-cycle and five-cycle TEAs, a considerably harder problem, which the prior GA approach failed to solve.

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Cryptanalysis of TEA Using Quantum-Inspired Genetic Algorithms

Cryptology deals with the design and analysis of secure communication and information management systems. Cryptography protects vital information from adversaries by the process of encryption and cryptanalysis provides adversaries information being communicated by exploiting cryptographic weaknesses. Cryptography is the key technology which is used in various information security applications to achieve security solutions such as confidentiality, authenticity, integrity, availability and non repudiation. Nature inspired computing applied successfully in various artificial intelligence and pattern recognition problems of various fields gives an inspiration to apply in cryptology. Evolutionary computing is being applied nowadays to achieve solutions of cryptographic and cryptanalytic problems. In this paper, we present brief on cryptosystem and overview on applications of genetic algorithms in cryptology. Findings show that the work on nature inspired computing in cryptology is minimal but the applications of genetic algorithms are increasing. The genetic algorithms are not only applied on less complex and classical ciphers but some block ciphers are also attempted for their solutions. Further insight research is needed to tackle various problems of modern cryptography using genetic or other evolutionary computing techniques.

Applications of Genetic Algorithms in Cryptology

In this paper, we present a new approach for cryptanalysis of four-round DES based on genetic algorithm. An efficient fitness measure is used to find some optimum keys with higher fitness values. Some valuable bits in these optimum keys which generate apparent deviation from the other observed bits will turn up. Then, these valuable bits can be applied to find other bits. The results indicate that genetic algorithm is successful at breaking the four-round DES cipher, but perhaps more significantly, this is a promising method applied to break other Feistel block cipher.

Jun Song

Papers

Cryptanalysis of Four-Round DES Based on Genetic Algorithm