PPS: Privacy-preserving statistics using RFID tags

As RFID applications are entering our daily life, many new security and privacy challenges arise. However, current research in RFID security focuses mainly on simple authentication and privacy-preserving identification. In this paper, we discuss the possibility of widening the scope of RFID security and privacy by introducing a new application scenario. The suggested application consists of computing statistics on private properties of individuals stored in RFID tags. The main requirement is to compute global statistics while preserving the privacy of individual readings. PPS assures the privacy of properties stored in each tag through the combination of homomorphic encryption and aggregation at the readers. Re-encryption is used to prevent tracking of users. The readers scan tags and forward the aggregate of their encrypted readings to the back-end server. The back-end server then decrypts the aggregates it receives and updates the global statistics accordingly. PPS is provably privacy-preserving. Moreover, tags can be very simple as they are not required to perform any computation, but only to store data.