@inproceedings{he2011preventing, author = {He, Yeye and Barman, Siddharth and Naughton, Jeffrey}, title = {Preventing Equivalence Attacks in Updated, Anonymized Data}, booktitle = {Proceedings of International Conference on Data Engineering (ICDE)}, year = {2011}, month = {January}, abstract = {In comparison to the extensive body of existing work considering publish-once, static anonymization, dynamic anonymization is less well studied. Previous work, most notably m-invariance, has made considerable progress in devising a scheme that attempts to prevent individual records from being associated with too few sensitive values. We show, however, that in the presence of updates, even an m-invariant table can be exploited by a new type of attack we call the “equivalenceattack.” To deal with the equivalence attack, we propose a graph-based anonymization algorithm that leverages solutions to the classic “min-cut/max-flow” problem, and demonstrate with experiments that our algorithm is efficient and effective in preventing equivalence attacks.}, url = {http://approjects.co.za/?big=en-us/research/publication/preventing-equivalence-attacks-in-updated-anonymized-data/}, edition = {Proceedings of International Conference on Data Engineering (ICDE)}, }