PDDL: Proactive Distributed Detection and Localization Against Stealthy Deception Attacks in DC Microgrids

With the rapid development of the information and communication technology in DC microgrids (DCmGs), the threat of deception attacks has been widely recognized. However, the stealthy deception attacks, which can hide the actual attack impact from the system operator as in the Stuxnet accident, have not yet been well studied. Towards this end, this paper proposes a proactive distributed detection and localization (PDDL) framework to defend against the stealthy deception attacks. The attack detection is achieved by observing the attack impact that is quantified as the voltage balancing deviation (VBD) and current sharing deviation (CSD) in DCmGs. Once any anomaly is perceived, the proactive perturbation on primary control gains (PCGs) will be activated to invalidate the previously inferred PCGs of the attacker, under which the constructed stealthy deception attacks may be located by the unknown input observer (UIO) based locators. To maximize the locatability of attacks while limiting the induced transient fluctuations on system states, an optimization problem is formulated to determine the PCG perturbation magnitude. Finally, the effectiveness of the PDDL framework is verified through extensive hardware-in-the-loop (HIL) based simulations and systematic full-hardware experimental studies.

Automated summary

In this paper, a proactive distributed detection and localization (PDDL) framework is proposed to defend against stealthy deception attacks in DC microgrids. Attack detection is achieved by observing voltage balancing deviation and current sharing deviation in DC microgrids. Once an anomaly is detected, a proactive perturbation is applied to the primary control gains to invalidate the inferred gains of the attacker, and the constructed stealthy deception attacks can be located using unknown input observer (UIO) based locators. An optimization problem is formulated to determine the magnitude of the perturbation to maximize attack locatability while limiting transient fluctuations on system states. The effectiveness of the PDDL framework is verified through hardware-in-the-loop (HIL) simulations and full-hardware experimental studies.