Privacy-preserving pattern matching for anomaly detection in RFID anti-counterfeiting

Authors:
Florian Kerschbaum;Nina Oertel
Affiliations:
SAP Research, Karlsruhe, Germany;SAP Research, Karlsruhe, Germany and Business Administration and Information Systems, University of Mannheim, Germany
Venue:
RFIDSec'10 Proceedings of the 6th international conference on Radio frequency identification: security and privacy issues
Year:
2010

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Abstract

Traces of RFID-equipped item can be used to detect counterfeits. Nevertheless companies are reluctant to share the necessary traces, since it is unclear what can be inferred from them. In this paper we present a provably secure pattern matching algorithm that can be used for distributed anomaly detection. We improve performance and detection capabilities compared to competing approaches by storing partial, malleable information on the RFID tag.