A cryptanalytic attack on Vigenère cipher using genetic algorithm (original) (raw)
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Application of Genetic Algorithm in Cryptanalysis of Mono-alphabetic Substitution Cipher
"Today, security is a vital concern in computer science, cryptography is used vastly for implementation of the same. Cryptanalysis is a process in which the security is attempted to breach and the complexity of this process is considered as security measurement. As cryptographic algorithm is open to all, the whole strength lies in the complexity of the key i.e. efforts to crack the key. Mostly the strength of the key is shown through its length, eventually the number of communication (Brute- force method). Genetic algorithms are considered to be a tool for meta heuristic applications. In this work an attempt is made to carry out cryptanalysis, through genetic algorithms. In this, mono-alphabetic substitution cipher technique is considered. The experiment is carried out for four key samples, and attempt to break with variations in genetic operators i.e. selection, crossover and mutation. Regarding variations, for selection- random with elitism, roulette wheel and tournament options are used, for crossover - 1 -point, 2-point and Uniform options are used, with interchanging mutation. Dr. Prabha Shreeraj Nair""Application of Genetic Algorithm in Cryptanalysis of Mono-alphabetic Substitution Cipher"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2191.pdf Article URL: http://www.ijtsrd.com/computer-science/other/2191/application-of-genetic-algorithm-in-cryptanalysis-of-mono-alphabetic-substitution-cipher/dr-prabha-shreeraj-nair"
A Generic Genetic Algorithm to Automate an Attack on Classical Ciphers
International Journal of Computer Applications, 2013
The work presented in this paper describes a generic genetic algorithm called DUREHA's (Dominance, Universal stochastic sampling and Rank-based Emulation of a Heuristic Algorithm) Algorithm for cryptanalysis of classical ciphers. The underlying objective of this paper is to automate the process of cryptanalysis in order to render salvage of time, and resources available, preserve population diversity, minimize the convergence rate and control mutation rates. While numerous algorithms have been proposed to automate this process for variegated ciphers, these approaches are yet isolated from each other. The existence of a generic algorithm to cryptanalyze any type of cipher is yet not true. The algorithm proposed in this paper aspires to address such issues. The implementation and experimentation of the proposed algorithm is accomplished using three types of classical ciphers namely monosubstitution, poly-substitution and columnar transposition. The theoretical validation and experimental results indicate that the proposed algorithm is able to decrypt the ciphers by reclaiming80.71% ,87.31%and 77.66% of letters in correct position in Mono-substitution, Columnar Transposition and Vignere cipher respectively. It is also able to distinguish between the three types of ciphers correctly and is able to correctly control the mutation andconvergence rates and preserve population diversity.
Using Genetic Algorithm to break a mono - alphabetic substitution cipher
IEEE Conference on Open Systems, 2010
Genetic algorithms (GAs) are a class of optimization algorithms. GAs attempt to solve problems through modeling a simplified version of genetic processes. There are many problems for which a Genetic Algorithm approach is useful. It is, however, undetermined if cryptanalysis is such a problem. Therefore, this work trying to explore the use of Genetic Algorithms in cryptography. The focus is
Key Generation for Vigenere Ciphering Based on Genetic Algorithm
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences
Cryptography is a science securing of information. Encryption requires impregnable keys to encrypt or decrypt data these keys should be unpredictable and not easily to break. In this research we use genetic algorithm to generate keys for vigenere cipher. The best key is used to perform encryption. The keys created by genetic algorithm are tested for randomness by using the entropy test. The entropy calculation shows that randomness of key generated based on genetic processing is better than chosen key in the classical vigenere cipher.
A New Approach of Known Plaintext Attack with Genetic Algorithm
WSEAS Transactions on Computers archive, 2018
Cryptanalysis of modern cryptosystems is viewed as NP-Hard problem. Block ciphers, a modern symmetric key cipher are characterised with the nonlinearity and low autocorrelation of their structure. In literature, various attacks were accomplished based on traditional research algorithms such the brute force, but results still insufficient especially with wide instances due to resources requirement, which increase with the size of the problem. Actual research tends toward the use of bio-inspired intelligence algorithms, which are heuristic methods able to handle various combinatorial problems due to their optimisation of search space and fast convergence with reasonable resource consumption. The paper presents a new approach based on genetic algorithm for cryptanalysis of block ciphers; we focuses especially around the problem formulation, which seems a critical factor that depends the attack success. The experiments were accomplished on various set of data; the obtained results indic...
Genetic Algorithms are stochastic algorithms. They are based upon Darwinian evolution theory. In genetic algorithms, individuals are binary digits or of some other set of symbols drawn from a finite set. As computer memory is made up of array of bits, anything can be stored in a computer and can also be encoded by a bit string of sufficient length. Each of the encoded individuals in the population can be viewed as a representation, according to an appropriate encoding of a particular solution to the problem. For Genetic Algorithms to find a best optimum solution, it is necessary to perform certain operations over these individuals. A genetic algorithm contains three operators: Selection, Crossover and Mutation. This paper presents the impact of different mutation rates for different population size. It is shown that such algorithm could be used to discover the key for a simple substitution cipher. The focus is to be on a single mono substitution cipher. The frequency analysis is used as an essential factor in the objective function.
The Applications of Genetic Algorithms in Cryptanalysis
1996
This thesis describes a method of deciphering messages encrypted with rotor machines utilising a Genetic Algorithm to search t h e k eyspace. A tness measure based on the phi test for non randomness of text is described and the results show that an unknown three rotor machine can generally becryptanalysed with about 4000 letters of ciphertext. The results are compared to those given using a previously published technique and found to be superior. P(Type I error) = = P(X 2 S 1 j 2 ):
Breaking Transposition Cipher with Genetic Algorithm
2007
The aim of the research presented in this paper is to investigate the use of genetic algorithm in the cryptanalysis of transposition cipher. The applicability of genetic algorithms for searching the key space of encryption scheme is studied. The frequency of bigram and trigram is used as an essential factor in objective function. Ill. 1, bibl. 8 (in Lithuanian; summaries in English, Russian and Lithuanian).