太赫兹科学与电子信息学报2025，Vol.23Issue(5)：482-488,7.DOI:10.11805/TKYDA2024383
数据显隐性关系驱动的敏感数据泄露风险预测
Sensitive data leakage risk prediction driven by data explicit and implicit relationships
摘要
Abstract
With the rapid development of Internet of Things(IoT),big data,and Artificial Intelligence(AI)technologies,massive amounts of data are being generated and utilized on an unprecedented scale.These data contain a large amount of sensitive information,and how to securely store sensitive data has become a realistic problem that needs to be solved.The existing data storage schemes usually focus on the direct protection of sensitive data,while ignoring the leakage risks associated with explicit and implicit associations between sensitive and non-sensitive data.The explicit and implicit relationships among data are deeply analyzed from the perspective of information entropy,and a method is proposed to quickly assess the explicit and implicit relationships and predict the leakage risk of sensitive data.By introducing the information Lift Ratio(LR)and the Probability of Information Control(PIC),the method can effectively identify the influence of non-sensitive data on the risk of sensitive data leakage.In the simulation experiments,the maximum single-attribute LR in the Statistical Property Dataset(SPD)is 0.308,and the joint-attribute LR can be up to 0.891,and the predicted value of the sensitive data leakage risk is significantly improved,up to 23.2%.The simulation results show that the method can effectively identify and cope with the security risks caused by explicit and implicit relationships,thus significantly improving the overall security level of sensitive data storage.关键词
信息熵/显隐性关系/风险评估/数据关联性/安全策略Key words
information entropy/explicit and implicit relationship/risk assessment/data correlation/security policy分类
计算机与自动化引用本文复制引用
梁花,靳敏,严华,韩世海,李玮..数据显隐性关系驱动的敏感数据泄露风险预测[J].太赫兹科学与电子信息学报,2025,23(5):482-488,7.基金项目
国网重庆市电力公司重点研发项目(2023渝电科技59号) （2023渝电科技59号）
