A Color Image Encryption Algorithm Based on Compressive Sensing and Block-Based DNA Coding

Abstract

Image encryption is an effective method to prevent images from being captured or stored illegally. With the increasing demand for image security and transmission efficiency, this paper proposes a color image encryption algorithm based on chaotic systems, which combines block-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DNA</i> coding and compressive sensing. Firstly, the plain image is compressed using compressive sensing (CS) to obtain three measurement value matrices, which are then quantized into integer matrices and permuted by the method of the Josephus problem. Subsequently, the scrambled measurement value matrices are divided into subblocks. These subblocks are encoded by random <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DNA</i> rules, diffused by chaotic sequences-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DNA</i> operations, and dynamically decoded. It is worth noting that the initial values of the chaotic systems used for the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DNA</i> operations and the generation of the measurement matrices depend on the plain image, which enables our algorithm to withstand well the chosen-plaintext attacks and the known-plaintext attacks. Moreover, we utilize singular value decomposition ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SVD</i> ) to optimize the measurement matrices to enhance the reconstruction quality of the encrypted image. Simulation results and security analysis show that the algorithm has excellent compression and encryption performance and is resistant to various typical attacks.