数据共享模式下个人档案数据隐私泄露研究及仿真

Research and simulation of personal file data privacy disclosure under data sharing mode

为有效应对受限数据共享环境下个人档案数据隐私泄露问题,在研究了受控数据共享技术、总体唯一性模型的基础上,该文提出将受控的数据共享与数据去识别技术相结合,从而在提供高质量数据的同时提升系统可扩展性。同时提出减少候选解数量和降低风险计算复杂性两个优化策略,以提升系统运行效率。通过仿真及分析可知,所提方法数据质量及运行时间与k-匿名算法相比均有所改善,仿真结果进一步验证了所提方法的有效性。

In order to effectively deal with the privacy leakage risk under the restricted data sharing environment,based on the study of controlled data sharing technology and the overall uniqueness model,this paper proposes the combination of controlled data sharing and data recognition technology,so as to provide high-quality data and improve the system scalability. At the same time,two optimization strategies are proposed to reduce the number of candidate solutions and reduce the complexity of risk calculation to improve the efficiency of the system. Through simulation and analysis,the data quality and running time of the proposed method are improved compared with k-anonymous algorithm. The simulation results further verify the effectiveness of the proposed method.