Research on Dynamic Selection Strategies of Encryption Algorithms under Deep Learning Frameworks

Abstract

This article focuses on the dynamic selection strategies of encryption algorithms under the framework of deep learning. Firstly, the current development status of deep learning and the security challenges it faces were expounded, emphasizing the crucial role of encryption algorithms in ensuring the security of deep learning data. Then, common encryption algorithms are classified and introduced, and their characteristics and applicable scenarios are analyzed. An in-depth discussion was conducted on multiple factors influencing the dynamic selection of encryption algorithms, including data characteristics, computing resources, and security requirements. On this basis, a dynamic selection strategy for encryption algorithms based on multi-factor comprehensive evaluation is proposed. The architecture design, selection process and decision-making mechanism of this strategy are elaborated in detail. Finally, the optimization direction and future development trend of the dynamic selection strategy were prospected.