Channel-State-Based Fingerprinting Against Physical Access Attack in Industrial Field Bus Network
Pengfei Liu, Yang Liu, Xiangming Wang, Chao Fang, Xiaohong Guan, Ting Liu
Abstract
The development of Industrial Internet of Things has made industrial control systems more vulnerable to cyber attacks. Many defense measures have been proposed to prevent attacks in upper IP-based networks. However, the security of underlying field bus networks has not received enough attention. Adversaries could tap intrusive devices into the field bus network via unauthorized physical access. As adversaries’ behaviors could be highly concealed when they are eavesdropping or camouflaging, it is challenging and costly to identify these inactive intrusive devices through the network traffic. However, inevitable changes in channel state caused by intrusive devices could be leveraged to detect unauthorized physical access. This article theoretically proves that the transmitted signal’s voltage amplitude would vary after tapping intrusive devices into the field bus network. Leveraging the signal’s variation, we propose an unauthorized physical access detection method via fingerprinting the channel state. Specifically, we adopt weak signal processing technologies to recover the signal’s weak variation and extract its features for detection. The effectiveness of the proposed detection method is validated based on a real testbed. Moreover, simulation experiments with diverse settings demonstrate that the proposed detection method could successfully detect intrusive devices under different scenarios.