A Novel 5-D-Chaotic Encryption Algorithm Based on Dual Memristive Hopfield Neural Network With Weight Switching Mechanism Using Peano Curve

In the digital era, the protection of digital images is of paramount importance. This paper proposes a novel 5D-chaotic Encryption Algorithm Based on Dual Memristive Hopfield Neural Network with Weight Switching Mechanism (DMHNN-WSM) , which can operate using dual memristors simultaneously and thereby enhances system performance. Sub-sequently, this system is applied to a new symmetric image encryption algorithm. First, the DMHNN-WSM chaotic system is utilized to generate a five-dimensional chaotic sequence, which is then processed to produce the encryption key. In the image scrambling algorithm, this paper proposes a multi-level interleaved scrambling method, specifically involving the interleaved execution of vector-level cyclic shifting, pixel-level swapping, and block-level scrambling. In the design of block-level scrambling in this paper, the idea of ZigZag transform is borrowed. Combined with the Peano curve to map the two-dimensional plane to a one-dimensional straight line, a block-level scrambling algorithm within the channel is constructed. Meanwhile, the Peano curve is further used for cross-channel scrambling with lifting height.In the image diffusion algorithm, chaotic sequences are used to perform XOR operations on the image. Ultimately, the NPCR (Number of Pixels Change Rate) of the encrypted image can reach up to 99.6089%, and the UACI (Unified Average Changing Intensity) can reach 33.4692%. The information entropy of 512×512 images can reach 7.9993, while that of 256×256 images can reach 7.9972. Quantitative analysis of multiple security indicators demonstrates the effectiveness of the proposed encryption scheme.