Implication of Genetic Algorithm in Cryptography to Enhance Security

In today’s age of information technology secure transmission of information is a big challenge. Symmetric and asymmetric cryptosystems are not appropriate for high level of security. Modern hash function based systems are better than traditional systems but the complex algorithms of generating inver...

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Published inInternational journal of advanced computer science & applications Vol. 9; no. 6
Main Authors Nazeer, Muhammad Irshad, Ali, Ghulam, Ahmed, Noor, Bhatra, Rakhi, Ahmed, Raheel, Ismail, Muhammad
Format Journal Article
LanguageEnglish
Published West Yorkshire Science and Information (SAI) Organization Limited 2018
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ISSN2158-107X
2156-5570
2156-5570
DOI10.14569/IJACSA.2018.090651

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Abstract In today’s age of information technology secure transmission of information is a big challenge. Symmetric and asymmetric cryptosystems are not appropriate for high level of security. Modern hash function based systems are better than traditional systems but the complex algorithms of generating invertible functions are very time consuming. In traditional systems data is being encrypted with the key but still there are possibilities of eavesdrop the key and altered text. Therefore, key must be strong and unpredictable, so a method has been proposed which take the advantage of theory of natural selection. Genetic Algorithms are used to solve many problems by modeling simplified genetic processes and are considered as a class of optimization algorithms. By using Genetic Algorithm the strength of the key is improved that ultimately make the whole algorithm good enough. In the proposed method, data is encrypted by a number of steps. First, a key is generated through random number generator and by applying genetic operations. Next, data is diffused by genetic operators and then logical operators are performed between the diffused data and the key to encrypt the data. Finally, a comparative study has been carried out between our proposed method and two other cryptographic algorithms. It has been observed that the proposed algorithm has better results in terms of the key strength but is less computational efficient than other two.
AbstractList In today’s age of information technology secure transmission of information is a big challenge. Symmetric and asymmetric cryptosystems are not appropriate for high level of security. Modern hash function based systems are better than traditional systems but the complex algorithms of generating invertible functions are very time consuming. In traditional systems data is being encrypted with the key but still there are possibilities of eavesdrop the key and altered text. Therefore, key must be strong and unpredictable, so a method has been proposed which take the advantage of theory of natural selection. Genetic Algorithms are used to solve many problems by modeling simplified genetic processes and are considered as a class of optimization algorithms. By using Genetic Algorithm the strength of the key is improved that ultimately make the whole algorithm good enough. In the proposed method, data is encrypted by a number of steps. First, a key is generated through random number generator and by applying genetic operations. Next, data is diffused by genetic operators and then logical operators are performed between the diffused data and the key to encrypt the data. Finally, a comparative study has been carried out between our proposed method and two other cryptographic algorithms. It has been observed that the proposed algorithm has better results in terms of the key strength but is less computational efficient than other two.
Author Ahmed, Noor
Ismail, Muhammad
Ahmed, Raheel
Bhatra, Rakhi
Ali, Ghulam
Nazeer, Muhammad Irshad
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crossref_primary_10_1111_exsy_13334
crossref_primary_10_1002_cpe_7691
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Snippet In today’s age of information technology secure transmission of information is a big challenge. Symmetric and asymmetric cryptosystems are not appropriate for...
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SubjectTerms Comparative studies
Computer systems
Cryptography
Eavesdropping
Genetic algorithms
Hash based algorithms
Operators (mathematics)
Optimization
Random numbers
Security
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