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.

Muhammad Irshad Nazeer, Ghulam Ali Mallah, Noor Ahmed Shaikh, Rakhi Bhatra, Raheel Ahmed Memon and Muhammad Ismail Mangrio, “Implication of Genetic Algorithm in Cryptography to Enhance Security” International Journal of Advanced Computer Science and Applications(IJACSA), 9(6), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090651

@article{Nazeer2018,
title = {Implication of Genetic Algorithm in Cryptography to Enhance Security},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2018.090651},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090651},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {6},
author = {Muhammad Irshad Nazeer and Ghulam Ali Mallah and Noor Ahmed Shaikh and Rakhi Bhatra and Raheel Ahmed Memon and Muhammad Ismail Mangrio},
}