k-strong privacy for radio frequency identification authentication protocols based on physically unclonable functions

Kardaş, Süleyman and Çelik, Serkan and Bingöl, Muhammed Ali and Kiraz, Mehmet Sabır and Demirci, Hüseyin and Levi, Albert (2015) k-strong privacy for radio frequency identification authentication protocols based on physically unclonable functions. Wireless Communications and Mobile Computing, 15 (18). pp. 2150-2166. ISSN 1530-8669 (Print) 1530-8677 (Online)

[thumbnail of Kardas_et_al_Wireless_Communications_and_Mobile_Computing.pdf] PDF
Restricted to Registered users only

Download (1MB) | Request a copy


This paper examines Vaudenay's privacy model, which is one of the first and most complete privacy models that featured the notion of different privacy classes. We enhance this model by introducing two new generic adversary classes, k-strong and k-forward adversaries where the adversary is allowed to corrupt a tag at most k times. Moreover, we introduce an extended privacy definition that also covers all privacy classes of Vaudenay's model. In order to achieve highest privacy level, we study low cost primitives such as physically unclonable functions (PUFs). The common assumption of PUFs is that their physical structure is destroyed once tampered. This is an ideal assumption because the tamper resistance depends on the ability of the attacker and the quality of the PUF circuits. In this paper, we have weakened this assumption by introducing a new definition k-resistant PUFs. k-PUFs are tamper resistant against at most k attacks; that is, their physical structure remains still functional and correct until at most kth physical attack. Furthermore, we prove that strong privacy can be achieved without public-key cryptography using k PUF-based authentication. We finally prove that our extended proposal achieves both reader authentication and k-strong privacy.
Item Type: Article
Uncontrolled Keywords: RFID;security;privacy;physically unclonable function
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Albert Levi
Date Deposited: 23 Dec 2015 15:19
Last Modified: 26 Apr 2022 09:28
URI: https://research.sabanciuniv.edu/id/eprint/28531

Actions (login required)

View Item
View Item