FLOC 2018: FEDERATED LOGIC CONFERENCE 2018
Statistical Model Checking of Guessing and Timing Attacks on Distance-bounding Protocols

Authors: Musab A. Alturki, Max Kanovich, Tajana Ban Kirigin, Vivek Nigam, Andre Scedrov and Carolyn Talcott

Paper Information

Title:Statistical Model Checking of Guessing and Timing Attacks on Distance-bounding Protocols
Authors:Musab A. Alturki, Max Kanovich, Tajana Ban Kirigin, Vivek Nigam, Andre Scedrov and Carolyn Talcott
Proceedings:FCS Informal Proceedings
Editors: Charles Morisset and Limin Jia
Keywords:Distance-bounding protocols, Distance fraud, Probabilistic rewriting, Statistical model checking, Maude
Abstract:

ABSTRACT. Distance-bounding (DB) protocols were proposed to thwart relay attacks on proximity-based access control systems. In a DB protocol, the verifier computes an upper bound on the distance to the prover by measuring the time needed for a signal to travel to the prover and back. DB protocols are, however, vulnerable to distance fraud, in which a dishonest prover is able to manipulate the distance bound computed by an honest verifier. Despite their conceptual simplicity, devising a formal characterization of DB protocols and distance fraud attacks that is amenable to automated formal analysis is non-trivial, primarily because of their real-time and probabilistic nature. In this work, we present a framework, based on rewriting logic, for formally analyzing different forms of distance-fraud, including recently identified timing attacks. We introduce a generic, real-time and probabilistic model of DB protocols and use it to (mechanically) verify false-acceptance and false-rejection probabilities under various settings and attacker models through statistical model checking with Maude and PVeStA. Using this framework, we first accurately confirm known results and then define and quantitatively evaluate new guessing-ahead attack strategies that would otherwise be difficult to analyze manually.

Pages:13
Talk:Jul 08 12:00 (Session 38E: Formal Modelling & Analysis)
Paper: