Joint Compression and Encryption of Distributed Sources Based on Wavelet Transform and Semi-Tensor Product Compressed Sensing

Aiming at the shortage of data transmission security and efficiency in wireless distributed transient pressure testing system, a new distributed information source joint compression and encryption scheme is proposed in this paper by combining wavelet transform, semi-tensor product compressed sensing and hash chain. Firstly, the signals are decomposed into different components by wavelet transform. Then, the measurement matrix of semi-tensor product compressed sensing is updated with the hash chain related to plaintext, and its used to compress and encrypt the different wavelet components. Finally, the measurement results of the previous steps are scrambled by hash sequences for further encryption. In this paper, simulation test is carried out by using the shockwave signal measured in practice. The simulation results show that the scheme has good reconstruction accuracy and security. When the compression rate reaches 0.25, the scheme can reduce the storage space and the computing resources required by the measurement matrix to 1/32 and 1/8 of traditional distributed compressed sensing. The proposed scheme is a flexible and efficient joint compression and encryption framework, which can flexibly adjust the measurement number of different types of components to ensure important information is effectively measured, balance reconstruction quality, compression rate and system resource consumption.