Privacy Assurance in Data-Aggregation for Multiple MAX Transactions
Kim Le, Parmesh Ramanathan, Kewal K. Saluja · 2015
Mobile devices are now very popular in many applications, and there is a trend to use them in statistic surveys. The main technical issue is privacy assurance. In this paper, we propose a certification-based approach for privacy assurance in multiple transactions of a survey conducted by a third-party application (TPA), which wants to find the maximal values of private data of some member groups in a social society. In our proposal, the computation burden on an involved user to verify the privacy assurance does not increase with the number of users participating in the survey. Furthermore, similar to traditional surveys, the users only need to communicate with the TPA. These features distinguish our approach from the existing research in literature for secure multi-party computation.