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An Improved Genetic Algorithm for Developing Deterministic OTP Key Generator

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  • Ashish Jain
  • Narendra S. Chaudhari

Abstract

Recently, a genetic-based random key generator (GRKG) for the one-time pad (OTP) cryptosystem has been proposed in the literature which has certain limitations. In this paper, two main characteristics (speed and randomness) of the GRKG method are significantly improved by presenting the IGRKG method (improved genetic-based random key generator method). The proposed IGRKG method generates an initial pad by using linear congruential generator (LCG) and improves the randomness of the initial pad using genetic algorithm. There are three reasons behind the use of LCG: it is easy to implement, it can run efficiently on computer hardware, and it has good statistical properties. The experimental results show the superiority of the IGRKG over GRKG in terms of speed and randomness. Hereby we would like to mention that no prior experimental work has been presented in the literature which is directly related to the OTP key generation using evolutionary algorithms. Therefore, this work can be considered as a guideline for future research.

Suggested Citation

  • Ashish Jain & Narendra S. Chaudhari, 2017. "An Improved Genetic Algorithm for Developing Deterministic OTP Key Generator," Complexity, Hindawi, vol. 2017, pages 1-17, October.
    • Handle: RePEc:hin:complx:7436709
    DOI: 10.1155/2017/7436709
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    Cited by:

    1. Jingyi Liu & Xinxin Liu & Ba Tuan Le, 2019. "Rolling Force Prediction of Hot Rolling Based on GA-MELM," Complexity, Hindawi, vol. 2019, pages 1-11, June.

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