Meaningful data encryption scheme based on newly designed chaotic map and P-tensor product compressive sensing in WBANs

Aiming at the problem that the data encryption schemes applied in wireless body area networks (WBANs) lack crypticity, in this paper, a meaningful data encryption scheme by combining P-tensor product compressive sensing model, newly designed chaotic map and data embedding technology is presented. First, a novel one-dimensional discrete chaotic map is constructed through the stretching-and-squeezing mechanism to produce the key-controlled chaotic measurement matrix. Then, the generated measurement matrix and the 2-D Arnold scrambling are, respectively, utilized to encrypt and compress the plaintext wavelet packet coefficients, and the non-semantic secret image is obtained via the bidirectional Modulo-Plus diffusion operation under the control of secret code streams. Eventually, the matrix coding-based embedding approach is adopted to hide the secret data in a publicly available non-secret transmission medium to eliminate its statistical pseudo-random properties and obtain the meaningful ciphertext data. The theoretical analysis and experimental results indicate that under the premise of ensuring sufficient security, the performance of the proposed encryption scheme in terms of visual security, compressibility and encryption efficiency has been greatly improved, compared with existing schemes.

Automated summary

In this paper, a data encryption scheme for wireless body area networks (WBANs) is proposed, which combines compressive sensing model, chaotic map, and data embedding technology to improve efficiency and compressibility while ensuring security.