A probe into process-level attack detection in industrial environments from a side-channel perspective
Paper i proceeding, 2019

Process-level detection of cyberattacks on industrial control systems pertain to observing the physical process to detect implausible behavior. State-of-the-art techniques identify a baseline of the normal process behavior from historical measurements and then monitor the system operation in real time to detect deviations from the baseline. Evidently, these techniques are intended to be connected to the control flow to be able to acquire and analyze the necessary measurement data, which makes them susceptible to compromise by the attacker. In this paper, we approach process-level attack detection from a side-channel perspective, where we investigate the feasibility and efficacy of monitoring industrial machines through external sensors. The sensors measure physical properties of the process that are bound to change during a cyberattack. We demonstrate the viability of our approach through simulations and experiments on real industrial machines.

Industrial Control System


Anomaly Detection

Industrial Environment

Embedded System


Wissam Aoudi

Chalmers, Data- och informationsteknik, Nätverk och system

Albin Hellqvist

Student vid Chalmers

Albert Overland

Student vid Chalmers

Magnus Almgren

Chalmers, Data- och informationsteknik, Nätverk och system

ACM International Conference Proceeding Series


5th Annual Industrial Control System Security Workshop, ICSS 2019
San Juan, USA,

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