Research on Data Classification and Grading of Inherent Safety in Nuclear Power DCS Platform

As a national critical information infrastructure (CII), the security of nuclear power digital instrumentation and control system (DCS) is crucial. As cyberattacks continue to evolve, the security risks and compliance challenges of nuclear power DCS platforms have become increasingly prominent, directly threatening their availability, and there is an urgent need to strengthen endogenous security control. In order to balance the security and availability of the system, security control measures should be added in a targeted manner based on data classification and classification. However, the current data classification and grading standards have problems such as poor pertinence and weak operability. Considering the particular requirements of the nuclear power DCS platform, such as high availability, high reliability, and high real-time, endogenous safety risks are identified, and endogenous safety requirements are analyzed to guide the formulation of data classification and classification rules. Apply this rule to obtain the data classification and hierarchical catalog of the nuclear power DCS platform and formulate subdivided security control measures accordingly to ensure better endogenous security, which positively improves data security and reduces risks. The research results can also provide reference examples and guidance for CII systems in other fields.