Secure Re-publication of Dynamic Big Data
Dynamic data re-publication is now an emerging issue in data pub lishing due to the awareness of privacy disclosure in data sharing.Existing models such as k-anonymity and l-diversity only aim to provide data protec tion for single release.In practical, new data arrive continuously and up-to-date dataset should be released from time to time.The release of multiple anony mized datasets (microdata) allows the attackers to learn extra knowledge by cross examines the releases within a targeted timeframe.In this paper, we study the data re-publication of dynamic big data based on the m-invariance model.In particular, we reconstruct the existing model to support re-publication for big data.We consider re-publication with insertion, deletion and update of the ex isting records.Counterfeit records will be used to maintain the update pattern of all the releases and to increase the false information in the knowledge learned by the attacker from the released microdata.
privacy-preserving data publishing dynamic data re-publication big data privacy m-invariance
Kok-Seng Wong Myung Ho Kim
School of Computer Science and Engineering,Soongsil University,Information Science Building,Sangdo-Dong Dongjak-Gu,Seoul,South Korea 156-743
国际会议
The 5th International Symposium on Cyberspace Safety and Security ( CSS2013)(第五届国际网络空间安全和安保研讨会)
张家界
英文
468-477
2013-11-13（万方平台首次上网日期，不代表论文的发表时间）