Shape of the Cloak: Formal Analysis of Clock Skew-Based Intrusion Detection System in Controller Area Networks

TL;DR

This paper introduces a formal analysis of clock skew-based intrusion detection systems in automotive CAN networks, demonstrating a cloaking attack that can evade detection and validating the analysis through experiments on real vehicles.

Contribution

It provides the first formal models for clock skew-based IDSs in automotive CAN and evaluates the cloaking attack's effectiveness through both analysis and real-world testing.

Findings

Cloaking attack successfully evades detection in tested scenarios.

Formal models accurately predict attack success probabilities.

Experimental validation shows low prediction errors within 3-6%.

Abstract

This paper presents a new masquerade attack called the cloaking attack and provides formal analyses for clock skew-based Intrusion Detection Systems (IDSs) that detect masquerade attacks in the Controller Area Network (CAN) in automobiles. In the cloaking attack, the adversary manipulates the message inter-transmission times of spoofed messages by adding delays so as to emulate a desired clock skew and avoid detection. In order to predict and characterize the impact of the cloaking attack in terms of the attack success probability on a given CAN bus and IDS, we develop formal models for two clock skew-based IDSs, i.e., the state-of-the-art (SOTA) IDS and its adaptation to the widely used Network Time Protocol (NTP), using parameters of the attacker, the detector, and the hardware platform. To the best of our knowledge, this is the first paper that provides formal analyses of clock skew-based IDSs in automotive CAN. We implement the cloaking attack on two hardware testbeds, a prototype and a real vehicle (the University of Washington (UW) EcoCAR), and demonstrate its effectiveness against both the SOTA and NTP-based IDSs. We validate our formal analyses through extensive experiments for different messages, IDS settings, and vehicles. By comparing each predicted attack success probability curve against its experimental curve, we find that the average prediction error is within 3.0% for the SOTA IDS and 5.7% for the NTP-based IDS.