(p,k)匿名数据集的增量更新算法

A dynamic update algorithm on (p,k) anonymity

随着大数据时代的到来,数据数量呈指数形式增长,一次性发布所有的数据已无法满足实时掌握数据的需求,提出(p,k)匿名增量更新算法,动态更新匿名发布数据表。为避免数据动态更新时造成隐私泄露,算法利用加密技术对敏感属性进行保护,建立暂存表及临时表辅助待更新数据及时插入。(p,k)匿名增量更新算法改善了传统算法无法实时更新数据的问题,保证了数据的实时性,并利用加密技术增强了数据的隐私保护性。实验结果表明,(p,k)匿名增量更新算法在较少信息损失量以及较快更新速率的情况下,实现了数据实时更新的目标。

With the arrival of the era of big data,the number of data increases exponentially,onetime release of all data can no longer meet the needs of real-time data,so an incremental update algorithm on（p,k）anonymity is proposed to dynamically update anonymous publication data tables.In order to avoid privacy leakage when data is dynamically updated,the algorithm uses encryption technology to protect sensitive attributes.We create a temporary table and an interim table to aid the timely insertion of updated data.The incremental update algorithm on（p,k）anonymity improves the problem that traditional algorithms cannot update data in real time,ensures the real-time performance of data,and uses encryption technology to enhance data privacy protection.Experimental results show that the incremental update algorithm on（p,k）anonymity achieves the goal of real-time data update with less information loss and faster update rate.