Lossless image compression-encryption algorithm based on BP neural network and chaotic system

• Published in: Multimedia tools and applications Vol. 79; no. 27-28; pp. 19963 - 19992
• Main Authors: Yang, Feifei, Mou, Jun, Sun, Kehui, Chu, Ran
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-07-2020; Springer Nature B.V
• Subjects: Algorithms; Back propagation networks; Bandpass filters; Chaos theory; Circuits; Computer Communication Networks; Computer Science; Computer simulation; Data Structures and Information Theory; Encryption; Fractal analysis; Image compression; Lossless equipment; Multimedia Information Systems; Neural networks; Phase diagrams; Pseudorandom sequences; Special Purpose and Application-Based Systems; Lossless image compression-encryption; BP neural network; Fractional-order memristive BPF chaotic circuit; Zigzag confusion
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-020-08821-w

In this paper, a fractional-order memristive band-pass filter (BPF) chaotic circuit is constructed base on BPF chaotic circuit and fractional definition. The attractor and fractal characteristics are analyzed through phase diagrams and time domain response diagrams. In addition, randomness of the chaotic pseudo-random sequences is tested through NIST SP800–22 and correlation of sequence. According to the fractional-order chaotic system and Back-Propagation (BP) neural network, a lossless image compression-encryption algorithm is proposed. In this algorithm, the original image is compressed through BP neural network, and then the compressed image is encrypted by using Zigzag algorithm and xor operation. Numerical simulation results show that the proposed algorithm not only can effectively compression-encryption image, but also have the great security performances, which provides theoretical guide for the application of this algorithm in information safety, and secret communication field.