Privacy Preserving Utility Verification of Data Published

With modern collaborative data publishing techniques, the problem is that a central data publisher is liable for aggregating sensitive data from multiple parties then anonymizing it before publishing for data processing. In such scenarios, the user demands to know the utility of their published data since most anonymization techniques have side effects on data utility. Moreover, a corrupt data publisher is capable of misusing the collected data for their gains. We could call this an "insider attack". In this paper, we address this problem and briefly discuss a few proposed solutions.