Enhancing Security and Randomness of DNA Cryptosystem Generated by Using Mealy Machine

Authors

  • Gaverchand K
  • Venkatesan R SRM Institute of Science and Technology
  • Kavikumar Jacob Faculty of Universiti Tun Hussein Onn Malaysia
  • Yasmin A

Keywords:

Encryption, Decryption, Mealy Machine, DNA Computing

Abstract

In the current scenario, a vast amount of confidential data is stored and transmitted over the internet. Ensuring data security is crucial due to the multitude of threats and risks posed by hackers and intruders. The Deoxyribonucleic Acid (DNA) cryptosystem is employed as a secure method for data communication. This technique transforms confidential data (plaintext) into an unintelligible format (ciphertext) before transmitting it through vulnerable channels. The core objective of a DNA cryptosystem is to transmit ciphertext in the form of a DNA string, using a DNA encoding table in the intermediate process. This paper presents an innovative DNA cryptographic technique that relies on both a DNA encoding table and a Mealy machine. In this proposed model, a randomly generated Mealy machine and a DNA table are combined to enhance security and efficiency, ensuring randomness in the resulting ciphertext. The proposed DNA cryptosystem has undergone extensive testing and analysis, including comparisons, frequency distribution, security attacks. The randomness test discussed in the National Institute of Standards and Technology (NIST) test suite further affirms the encrypted data's randomness, demonstrating an average P-value of 0.72 that exceeds the performance of existing schemes. Besides, it ensures a secured cryptosystem by achieving an average avalanche effect of 79%. Accordingly, this proposed model offers greater security compared to existing DNA cryptosystems that use automata theory.

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Published

18-12-2024

Issue

Section

Articles

How to Cite

K, G., R, V., Jacob, K., & A, Y. (2024). Enhancing Security and Randomness of DNA Cryptosystem Generated by Using Mealy Machine. Journal of Soft Computing and Data Mining, 5(2), 245-263. https://penerbit.uthm.edu.my/ojs/index.php/jscdm/article/view/18715