Privacy Preserved Mobile Sensing Using Region-Based Group Signature

Mobile sensing receives lots of attention since it exploits sensors embedded in smartphones to gather information for quality improvement of daily life. In particular, mobile users (MUs) carrying smartphones act as queriers who request information provided by MUs who act as data collectors, and the data collection and delivery are facilitated by human mobility and ubiquity. However, additional privacy considerations rise in this paradigm, where MUs might not want to reveal their identities when providing some information at a specific position during a particular period. By adopting group signature, where any member of its group can sign a message on behalf of the entire group, the signer of the sensed information cannot be recognized, and thus, anonymity is preserved. The concept of group signature can be realized when introducing mobile edge computing, where base stations are clustered into a region to serve a group of MUs. In such region-based group signature, MUs located in the same region are grouped and thus are indistinguishable. Due to the localized movement feature of human, MUs might not frequently leave the current group and join a new group, which subsequently reduces the infamous rekeying overhead. We implement group signature on Android smartphones and conduct simulation experiments to investigate the performance of the proposed region-based grouping approach from the perspectives of rekeying overhead and delay. The simulation results show that the region-based grouping method is efficient. Moreover, the optimal group number for the minimization of rekeying overhead is suggested.