A comprehensive methodology referred to as DEFENDA – DEtection of FalsE and uNexpected Data Attacks – is proposed to quantify the integrity of data and to characterize the impact of false data on power systems. These attacks are referred to as unobservable or stealth false data injection (FDI) attacks, and they are crafted to bypass traditional bad data detection. DEFENDA’s vision is to quickly detect sensor manipulation attacks and correct false data. The project aims to contribute enhanced state-of-the-art cyber-physical security strategies for transmission system operation, where results will inform solution of similar problems including cyber-physical attack detection at generation, transmission, and distribution levels as well as in communication networks, banking systems, cloud computing and storage, and other critical infrastructures.
Download False Injection Dataset for IEEE 14, 118, 300 bus systems.