面向工业场景数据安全的优化卸载方法

The problem of security offloading in data transmission in industriai scenarios has gained wide attention. This paper is the first to integrate security policy as a decision variable into the optimization problem. It applies computational offloading principles and differential evolutionary algorithms, and proposes a data security offloading algorithm. Firstly, mathematical modeling conducted for four computing modes of industriai field devices:local computing, local edge computing, cross-plant edge computing in this paper, and cloud computing, as well as data security, and a data security offloading model is constructed by integrating multi-level security policies, task offloading, and resource allocation. Then the security-optimized offloading scheme is formed by designing the objective function of maximizing device satisfaction by considering the effects of tinte delay and security risk proba-bility. Finally, for this optimization problem, a data security offloading algorithm based on an improved differential evolution strategy is proposed to maximize the device satisfaction of the system while satisfying the optimal solution with the latency and security risk requirements. Compared with the GASORA, GSOJRA and DEDSTO-NS algorithms, the proposed algorithm enables the field devices to satisfy the delay and risk probability requirements. Furthermore, it improves the device satisfaction by 35% while guaranteeing data security. Simulation results confirm the effectiveness of the proposed method and bave some realistic application value.