Image encryption scheme using a new 4-D chaotic system with a cosinoidal nonlinear term in WMSNs

Abstract

To protect the sensitive data captured in the wireless media sensor networks (WMSNs), this paper propounds a novel data encryption scheme by employing a new chaotic system and the semi-tensor product compressive sensing model driven by a linear congruence generator. In this scheme, the coefficients yielded by sparsely decomposing the plaintext image onto a wavelet packet basis are firstly compressed using a key-controlled measurement matrix. To minimize the threat of various attacks, the compressed image is then subjected to bidirectional diffusion manipulation to conceal its statistical properties under the control of chaotic sequences. Additionally, it is worth explaining that a lightweight 4-D chaotic system with only one nonlinear term is designed to accommodate the resource-constrained situation in WMSNs. Finally, theoretical analysis and investigations affirm its significant enhancement in visual security, compressibility, and encryption efficiency. Moreover, the proposed scheme is significantly superior to existing relevant encryption ones.

Image encryption scheme based on pseudo-DWT and cubic S-box

“…In recent years, deep learning has also demonstrated its powerful potential in the field of image encryption. For example, the combination of deep learning and chaotic systems [5][6][7][8][9] can increase encryption performance.…”