With the rapid development of Internet of Things (IoT) and Artificial Intelligence (AI) technologies, information security has become a critical issue. To develop a highly secure image encryption transmission system, this study proposes a novel key generation mechanism based on the combination of fractional-order chaotic system synchronization control and the SHA-256 algorithm. This proposed method dynamically generates high-quality synchronous random number sequences and is combined with the Advanced Encryption Standard (AES) algorithm. To quantitatively evaluate the mechanism, the generated sequences are tested using NIST SP 800-22, ENT, and DIEHARD suites. The comparative results show that the key generation mechanism produces sequences with higher randomness and unpredictability. In the evaluation of image encryption, histogram distribution, information entropy, adjacent pixel correlation, NPCR, and UACI are used as performance metrics. Experimental results show that the histogram distributions are uniform, the values of information entropy, NPCR, and UACI are close to their ideal levels, and the pixel correlation is significantly reduced. Compared to recent studies, the proposed method demonstrates higher encryption performance and stronger resistance to statistical attacks. Furthermore, the system effectively addresses key distribution and management problems inherent in traditional symmetric encryption schemes. These results validate the reliability and practical feasibility of the proposed approach.
Chen et al. (Fri,) studied this question.