Research on a Privacy-Aware Data Processing Framework for Large-Scale Distributed Systems

Abstract The widespread adoption of large-scale distributed systems has promoted the efficient circulation and processing of multi-source data; however, the risk of data privacy leakage has become a core bottleneck constraining their development. This paper focuses on theoretical research on privacy-aware data processing. Based on the data processing characteristics of distributed systems and the core requirements of privacy protection, it constructs a privacy-aware data processing framework at the theoretical level, clarifies the framework’s core layers and theoretical connotations, and systematically analyzes the theoretical linkages among key enabling technologies. Through a literature review of existing related work, this paper identifies the current research status and gaps in distributed data processing and privacy protection, providing theoretical support for the collaborative optimization of data processing and privacy protection in large-scale distributed systems.