NDLI: How to detect cloned tags in a reliable way from incomplete RFID traces

Content Provider	IEEE Xplore Digital Library
Author	Lehtonen, M. Michahelles, F. Fleisch, E.
Copyright Year	2009
Description	Author affiliation: Information Management, ETH Zürich, 8092, Switzerland (Lehtonen, M.; Michahelles, F.; Fleisch, E.)
Abstract	Cloning of RFID tags may lead to considerable financial losses and worse reputation in many commercial applications, while being attractive for adversaries. One way to address tag cloning is to use the visibility that RFID traces provide to detect cloned tags as soon as they enter the system. However, RFID traces always represent historic events without giving certainty where the traced objects currently really are. Furthermore, imperfect read rates can lead to missing reads. As a result, the visibility is not always perfect, which makes detection of cloned tags harder and less reliable. This paper presents a series of probabilistic techniques to enable reliable detection of cloned tags in cases where the visibility is incomplete. Our hypothesis is that the events generated by cloned tags cause rare or abnormal events that can be detected when the process that generates the legitimate events is understood. The presented techniques are studied in a comprehensive simulation study of a real-world pharmaceutical supply chain. Our findings suggest that reliable detection of cloned tags is possible if missing reads are addressed and the supply chain is precisely modeled.
Starting Page	257
Ending Page	264
File Size	1037749
Page Count	8
File Format	PDF
ISBN	9781424433377
DOI	10.1109/RFID.2009.4911190
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Technology management Event detection Supply chains Cloning Authentication Cryptography Counterfeiting RFID tags Radiofrequency identification Pharmaceuticals
Content Type	Text
Resource Type	Article

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