STD: Sensor-Oriented Temporal Detector Against Multi-Type Load Redistribution Attacks in Smart Grid

The modern smart grid integrates information and communication technology (ICT) with electronic devices, but this integration introduces cybersecurity risks. Load measurements, crucial for grid operation, are vulnerable to attacks, particularly Load Redistribution Attacks (LRAs). LRAs maliciously alter load readings to mislead control systems without being detected by conventional methods. This paper first introduces two advanced LRA variants: a stealthy-enhanced LRA designed to bypass sophisticated data-driven detectors, and an impact-enhanced LRA engineered to cause significant operational disruptions, such as increased generation costs. To address these evolving threats, we propose a novel Sensor-oriented Temporal Detector (STD). Unlike existing methods that often rely on aggregate data or labeled attack examples, our STD focuses on the unique temporal patterns of individual sensor measurements. It achieves this by combining principal subspace projection to identify normal data subspaces with sequential change extraction to detect subtle deviations over time. This approach allows the STD to identify various LRA types effectively, even without prior knowledge of attack signatures. Extensive simulations validate the destructive impact of our proposed LRA variants and demonstrate the superior detection performance of the STD against these sophisticated attacks.