DocumentCode
3316240
Title
How to detect cloned tags in a reliable way from incomplete RFID traces
Author
Lehtonen, Mikko ; Michahelles, Florian ; Fleisch, Elgar
Author_Institution
Inf. Manage., ETH Zurich, Zurich
fYear
2009
fDate
27-28 April 2009
Firstpage
257
Lastpage
264
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.
Keywords
probability; radiofrequency identification; RFID tags cloning; cloned tags detection; incomplete RFID traces; probabilistic techniques; real-world pharmaceutical supply chain; Authentication; Cloning; Counterfeiting; Cryptography; Event detection; Pharmaceuticals; RFID tags; Radiofrequency identification; Supply chains; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
RFID, 2009 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
978-1-4244-3337-7
Electronic_ISBN
978-1-4244-3338-4
Type
conf
DOI
10.1109/RFID.2009.4911190
Filename
4911190
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