一种基于风险要素的图嵌入数据安全审计方案OA

With the increasing complexity of data security risks in big data environments,existing data security audit technologies are limited by fragmented feature utilization and insufficient scalability,preventing comprehensive lifecycle risk coverage and thereby reducing risk detection efficiency.To address these challenges,a graph-embedded data security audit scheme based on risk elements(RE-GDSA)has been proposed.The scheme first constructs a security risk elements space comprising data attributes(D),user characteristics(U),carrier environment(C),and actions(A),achieving structured mapping of risk features throughout the entire data lifecycle.It then employs graph embedding technology to map these security risk elements into low-dimensional semantic vectors,constructs a cross-dimensional association model for integrated analysis,and achieves efficient risk detection.The feasibility of the scheme is validated through effectiveness and performance analysis.