Vulnerability aware graphs for RFID protocol security benchmarking

Security and privacy issues in Radio Frequency Identification (RFID) systems mainly result from limited storage and computation resources of RFID tags and unpredictable communication environment. Although many security protocols for RFID system have been proposed, most of them have various flaws. We propose a random graph-based methodology enabling automated benchmarking of RFID security. First, we formalize the capability of adversaries by a set of atomic actions. Second, Vulnerability Aware Graphs (VAGs) were developed to elaborate the interactions between adversaries and RFID systems, which are used to discover the potential attacks of adversaries via some paths on the graphs. The quantitative analysis on VAGs can predict the probability that the adversary leverages the potential flaws to perform attacks. Moreover, a joint entropy-based method is provided to measure the indistinguishability of RFID tags under passive attacks. Analysis and simulation were conducted to show the validity and effectiveness of VAGs.