基于关联规则的隐私泄露风险评估模型

Privacy Disclosure Risk Assessment Model Based on Association Rules

传统的信息安全风险评估较少涉及对背景知识关联分析所导致的隐私泄露风险。针对基于关联分析的大数据隐私泄露风险问题,以隐私资产、隐私威胁因子和隐私存储有效时间为要素建立隐私泄露风险指标体系、定义风险计算函数;通过对隐私库的关联规则及频繁项的分析,得出满足最小支持度阈值的关联概率,实现风险函数计算;最后,针对搜索数据进行实例验证,验证表明该模型可以有效评估风险,真实刻画隐私泄露风险大小。

The traditional information security risk assessment is less involved in the privacy msclosure nsx caused by association analysis of the background knowledge. For the problem of big data＇ s privacy disclosure based on association analysis, privacy asset, privacy threat factors and effective time for privacy storage were combined to establish risk index system of privacy disclosure. Besides, risk function was defined; with analysis association rules of privacy and frequent items , association probability of satisfying a minimum support threshold was generated; In addition, an example verification shows that the model can effectively evaluate privacy disclosure risk.