Cryptanalysis of Four-Round DES Based on Genetic Algorithm

Song, Jun; Zhang, Huanguo; Meng, Qiang; Wang, Zhangyi

doi:10.1109/wicom.2007.580

Cited by 32 publications

(20 citation statements)

References 12 publications

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“…The performance of the proposed algorithm is compared with cryptanalysis of four rounded DES using genetic algorithm [1]. GA is chosen for comparison because both are evolutionary algorithms and both have natural selection process.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Cryptanalysis of four-rounded DES using binary particle swarm optimization

Shahzad

Siddiqui

Khan

2009

Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation

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A highly efficient Binary PSO based cryptanalysis approach for four-rounded 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 proposed approach has shown promising results over cryptanalysis of DES performed using other methods such as Genetic Algorithm.

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Section: Simulation Resultsmentioning

confidence: 99%

“…In evolution process each particle modifies its velocity and position according to equations (1) and (2). The fitness function is based on the number of same bits in identical positions between original ciphertext C s generated by using real key and the ciphertext generated by using trial key C t [1].…”

Section: Proposed Techniquementioning

confidence: 99%

Cryptanalysis of four-rounded DES using binary particle swarm optimization

Shahzad

Siddiqui

Khan

2009

Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation

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“…Considering the cipher text attack only few keys are produced based on their cost function value which depends on the frequency of the letters. Cryptanalysis of Four round DES based on genetic algorithm is already implemented [13] .To find the optimum keys, an efficient fitness measure is used which is based on higher fitness values. The valuable bits in these optimum keys that generate some sort of deviation from the various observed bits will turn up and these valuable bits can be considered to find other bits .…”

Section: B Genetic Algorithmmentioning

confidence: 99%

“…This problem is solved effectively by Computational Intelligence, without searching the complete key space [1]. The optimization problems can also be solved by evolutionary techniques like Genetic Algorithm [8]. Evolution operations like crossover and mutation are not present in PSO.…”

Section: Introductionmentioning

confidence: 99%

The Particle Swarm Optimization Based Linear Cryptanalysis of Advanced Encryption Standard Algorithm

Dolly¹

2015

IJRITCC

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Abstract:-The tremendous development in internet technology, wireless communication and the type of internet capable devices has increased the amount of network usage .Millions of users are associated with the network and thus there is need for network security. The sensitive data that is deposited and transmitted on the internet need protection from attackers and eavesdroppers who perform illegal actions. Cryptography algorithms are the key factor of the security mechanisms used for data storage and uninterrupted network transmissions. The data security purely depends on the Cryptography algorithm hence the keys must be managed in a good way. Security mechanisms are developed when a threat to security is identified. To identify the security risk associated with AES algorithm, a computational intelligence based approach for known cryptanalysis of Advanced Encryption Standard algorithm is introduced. Particle swarm optimization based cryptanalysis is used much now a days because of its fast convergence rate. A PSO oriented cryptanalysis technique for breaking the key used in advance encryption standard algorithm is introduced. This approach is for known cipher text-only attack for an AES encryption system, where the key is deduced in a minimum search space in contrast to the Brute Force Attack. The key used in AES can be detected effectively with Particle Swarm Optimization

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“…An attack was reported by Garg [44] using genetic algorithm with ring crossover and other operators for the cryptanalysis on S-DES where GA perform far better than Brute Force search algorithm. Cryptanalysis of Simplified Data Encryption Standard Algorithm using GA was reported by Sharma and Song [45,46]. Normadic genetic algorithm for cryptanalysis of DES 16 was reported by Sathya et al [47].…”

Section: Cryptanalysis Of Block Ciphersmentioning

confidence: 99%

Applications of Genetic Algorithms in Cryptology

Ratan

2014

Advances in Intelligent Systems and Computing

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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.

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Cryptanalysis of Four-Round DES Based on Genetic Algorithm

Cited by 32 publications

References 12 publications

Cryptanalysis of four-rounded DES using binary particle swarm optimization

Cryptanalysis of four-rounded DES using binary particle swarm optimization

The Particle Swarm Optimization Based Linear Cryptanalysis of Advanced Encryption Standard Algorithm

Applications of Genetic Algorithms in Cryptology

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