Random Graph Based Benchmarking Methodology for RFID Security Protocols

Abstract

Security and privacy issues in current Radio Frequency Identification (RFID) systems mainly result from limited storage and computation resources of RFID tag sand unpredictable communication environment. Although many security protocols for RFID system have been proposed, most of them have various flaws. There is no effective method to locate those flaws in RFID protocols, or to predict adversaries' behaviors in advance. Some of the existing approaches have analyzed RFID protocols in qualitative, however the quantitative measurements of RFID security protocols are still challenging. In this paper, we propose a random graph-based methodology enabling benchmarking and automated analysis of RFID security protocols. Our graph-based method can elaborate the interaction between adversaries and RFID systems by generating the Vulnerability Aware Graphs (VAGs). VAGs discover the inherent flaws of RFID protocols, and reveal the details of adversaries' attacks via some paths on the graph. Moreover, the quantitative analyze on VAGs can predict the probability that the adversary leverages the potential flaws to perform attacks. We apply our method on a variant of the famous OSK protocol. Both the analysis and simulation results show the validity and effectiveness of VAGs.