Abstract—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 privacypreserving.
Moreover, tags can be very simple as they are not
required to perform any computation, but only to store data.