A new image encryption algorithm based on heterogeneous chaotic neural network generator and dna encoding

Gururaj Maddodi, Abir Awad, Dounia Awad, Mirna Awad, Brian Lee

Research output: Contribution to journalArticlepeer-review

73 Citations (Scopus)

Abstract

This paper presents a new combined neural network and chaos based pseudo-random sequence generator and a DNA-rules based chaotic encryption algorithm for secure transmission and storage of images. The proposed scheme uses a new heterogeneous chaotic neural network generator controlling the operations of the encryption algorithm: pixel position permutation, DNA-based bit substitution and a new proposed DNA-based bit permutation method. The randomness of the generated chaotic sequence is improved by dynamically updating the control parameters as well as the number of iterations of the chaotic functions in the neural network. Several tests including auto correlation, 0/1 balance and NIST tests are performed to show high degree of randomness of the proposed chaotic generator. Experimental results such as pixel correlation coefficients, entropy, NPCR and UACI etc. as well as security analyses are given to demonstrate the security and efficiency of the proposed chaos based genetic encryption method.

Original languageEnglish
Pages (from-to)24701-24725
Number of pages25
JournalMultimedia Tools and Applications
Volume77
Issue number19
DOIs
Publication statusPublished - 1 Oct 2018

Keywords

  • Chaos theory
  • DNA encoding
  • Encryption
  • Image security
  • Neural networks

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