A Sensitive Information Masking-Based Data Security Auditing Method for Chinese Linux Operating System

With the rapid development of information technology and the deepening of digitalization, operating systems are increasingly applied in critical information infrastructure, making data security issues particularly important. Traditional cloud storage auditing models based on third-party auditing authorities (TPA) face trust risks and potential data leakage during data integrity verification, which makes them inadequate to meet the dual requirements of high security and local controllability in the current information technology environment. To address this, this paper proposes a system-wide data security auditing method for the Chinese Linux operating system, constructing a lightweight and localized framework for sensitive information protection and auditing. By dynamically intercepting system calls and performing real-time content analysis, the method achieves accurate identification and visual masking of sensitive information, while generating corresponding audit logs. To overcome the efficiency bottleneck of traditional pattern matching in high-concurrency environments, this paper introduces a Chinese Aho-Corasick (AC) automaton-based character matching algorithm using a hash table to enhance the rapid retrieval capability of sensitive information. Experimental results demonstrate that the proposed method not only ensures controllable and auditable sensitive information but also maintains low system overhead and good adaptability, thereby providing a feasible technical path and implementation scheme for data security.