数据发布中的隐私保护研究综述

Survey of study on privacy-preserving data publishing

如何在发布涉及个人隐私的数据时保证敏感信息不泄露,同时又能最大程度地提高发布数据的效用,是隐私保护中面临的重大挑战。近年来国内外学者对数据发布中的隐私保护(privacy-preserving data publishing,PPDP)进行了大量研究,适时地对研究成果进行总结,能够明确研究方向。对数据发布领域的隐私保护成果进行了总结,介绍了常用的隐私保护模型和技术、隐私度量标准和算法,重点阐述了PPDP在不同场景中的应用,指出了PPDP可能的研究课题和应用前景。

When publishing the data set that is involved in personal privacy,the publisher should guarantee individual sensitive information security,simultaneously,as much as possible to improve the data usefulness and it is the great challenge in the privacy protection faces. In the recent years,the domestic and foreign scholars have conducted the extensive research. Carrying on the summary to the research results at the right moment,it can be clear about the research direction. This paper surveyed privacy protection achievements in the PPDP field,introduced the typical privacy protection model and technology, privacy metrics and algorithms. Focused on PPDP in different application scenarios,and pointed out that the PPDP possible research topics and application prospects.