A lossless compression and encryption scheme for sequence images based on 2D-CTCCM, MDFSM and STP

This paper proposes a lossless compression and encryption algorithm for sequence images based on adaptive inter-frames coding. This method can use the correlation in the time dimension to reduce redundant information. To increase the complexity of chaotic systems, this paper proposes a novel two-dimensional coupled and transformed Chebyshev cubic map (2D-CTCCM). Compared with existing chaotic systems, 2D-CTCCM exhibits better randomness and complexity. Moreover, this paper employs the Chinese remainder theorem in the process of lossless compression to obtain better compression performance. We extend the fractal sorting matrix to multi-dimensional space and apply it to the process of permutation. This paper proposes an improved semi-tensor product (STP) diffusion method to solve the problem that existing STP diffusion methods cannot resist chosen-plaintext attacks. Experimental results show that the performance of our algorithm is better than other lossless compression algorithms. It has strong key sensitivity and plaintext sensitivity and can resist brute-force attacks, statistical attacks, known-plaintext and chosen-plaintext attacks.