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Stream Cipher Based on Game Theory and DNA Coding

by Khaled Suwais*

Faculty of Computer Studies, Arab Open University, Riyadh, Saudi Arabia

* Corresponding Author: Khaled Suwais. Email: email

Intelligent Automation & Soft Computing 2022, 33(3), 1815-1834. https://doi.org/10.32604/iasc.2022.025076

Abstract

Securing communication over public communication channels is one of the challenging issues in the field of cryptography and information security. A stream cipher is presented as an approach for securing exchanged data between different parties through encryption. The core of stream cipher relies on its keystream generator, that is responsible for generating random and secure keystream of encrypting streaming data. Thus, the security of the keystream is measured by its randomness and its resistance to statistical and cryptanalytic attacks. As there is always a trade-off between the security and performance while designing new cryptographic primitives, we introduce a game theory-based stream cipher that performs fast and utilises the unpredictable behaviour of prisoners’ dilemma players to generate random sequences that serve as keystreams. To assure further security, the ciphertext is coded by DNA bases that are randomly scrambled at the beginning of every iteration of generating new keystream. The proposed stream cipher’s performance and security are thoroughly examined in terms of randomness, performance, and resistance to cryptanalytic attacks. The experiments show that our stream cipher can encrypt around 1230 Mbit/s. Statistically, our proposed stream cipher passed the NIST statistical tests successfully.

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Cite This Article

APA Style
Suwais, K. (2022). Stream cipher based on game theory and DNA coding. Intelligent Automation & Soft Computing, 33(3), 1815-1834. https://doi.org/10.32604/iasc.2022.025076
Vancouver Style
Suwais K. Stream cipher based on game theory and DNA coding. Intell Automat Soft Comput . 2022;33(3):1815-1834 https://doi.org/10.32604/iasc.2022.025076
IEEE Style
K. Suwais, “Stream Cipher Based on Game Theory and DNA Coding,” Intell. Automat. Soft Comput. , vol. 33, no. 3, pp. 1815-1834, 2022. https://doi.org/10.32604/iasc.2022.025076



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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