Application of multi-chaotic map cascade in video encryption to overcome statistical and differential attacks and performance evaluation

Abstract

The rapid proliferation of digital video across domains such as healthcare, surveillance, and communications has increased the demand for secure and efficient video encryption techniques. However, video data presents unique challenges, including large data volume and high spatial–temporal correlation, which limit the effectiveness and efficiency of conventional encryption approaches, particularly in real-time scenarios. In this context, the objective of this study is to evaluate the feasibility of a chaos-based video encryption in achieving both strong cryptographic security and acceptable computational performance. To accomplish this, the proposed scheme is tested through two controlled experiments. The evaluation focuses on cryptographic strength using the Number of Pixel Change Rate (NPCR) to measure sensitivity to minor input changes, the Unified Average Changing Intensity (UACI) to quantify average pixel intensity variation, and Shannon entropy to assess the randomness of the encrypted frames. In parallel, computational performance is analyzed through encryption time and throughput. The procedure involves frame extraction from video, followed by preprocessing to reduce pixel correlation, and subsequent application of the chaos-based encryption algorithm on a per-frame basis. The results from both experiments show NPCR values exceeding 99.5% and encrypted frame entropy of approximately 7.74 bits/pixel, indicating strong resistance to differential attacks and near-optimal randomness. However, the observed throughput of 0.07–0.09 frames per second highlights a limitation in meeting real-time processing requirements. These findings suggest that while the proposed scheme is cryptographically robust and suitable for offline or batch-processing applications.