Detecting Timing Attack on PMU Data utilizing Unwrapped Phase Angle and Low-Rank Henkel Matrix Properties
Imtiaj Khan, Virgilio Centeno

TL;DR
This paper presents a novel method to detect timing attacks on PMU data by analyzing unwrapped phase angles and low-rank Henkel matrix properties, effectively distinguishing them from false data injection attacks.
Contribution
It introduces a new detection approach combining phase angle analysis and low-rank matrix properties to identify timing attacks on PMUs, validated on IEEE 13 bus system.
Findings
Timing attack increases Henkel matrix approximation error by 700% for 3 sec delay.
Detection accuracy is high for delays of 2 seconds or more.
False data injection attacks do not significantly affect the Henkel matrix profile.
Abstract
Introduction of PMUs to cyber-physical system pro-vides accurate data acquisition, while posing additional risk of being the victim of cyber attack. Both False Data Injection Attack (FDIA) and GPS-spoofing or timing attack can provide malicious data to the cyber system, though these two attacks require different post-attack contingency plan. Thus accurate detection of timing attack and separating it from conventional FDIA has become a very important research area. In this article, a successful detection of timing attack mechanism is proposed. Firstly, a method to distinguish timing attack and FDIA using unwrapped phase angle data is developed. Secondly, utilizing low rank Henkel matrix property to differentiate timing attack from electrical events is also presented. Finally, an experimental validation of proposed model is performed on IEEE 13 bus system using simulated GPS-spoofing…
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Taxonomy
TopicsSmart Grid Security and Resilience · Power System Optimization and Stability · Power Systems Fault Detection
