The paper investigates blind false data injection attacks (FDIAs) on power grids, showing that for a connected DC branch‑flow model the residual‑sensitive subspace equals the weighted cycle space. This space is both necessary and sufficient for constructing complete stealthy attacks, revealing that only cycle‑space knowledge is required. The authors propose a benchmark, a measurement‑only reconstruction method, and extend the analysis to AC systems via a cycle manifold, demonstrating practical attack generation on GPUs.
By Xin Li, Chenhan Xiao, Jonathan Cohen, Aviad Elyashar, Yang Weng, Rami Puzis
arXiv:2606. 08473v1 Announce Type: new Abstract: False data injection attacks (FDIAs) introducing small measurement perturbations can still cause large deviations in power system state estimation when the injected signals align with the pseudo-null space of the system model.
By Xin Li, Chenhan Xiao, Jonathan Cohen, Aviad Elyashar, Yang Weng, Rami Puzis
arXiv:2606. 06347v1 Announce Type: cross Abstract: This paper addresses the problem of attack detection in cyber-physical systems without any knowledge of the plant model or its structure.
By Sribalaji C. Anand, Anh Tung Nguyen, George J. Pappas
arXiv:2606.
By Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang, Jinyuan Sun, Kevin Tomsovic
arXiv:2509.05259v2 Announce Type: replace
Abstract: Automatic Generation Control (AGC) plays a critical role in maintaining power balance across multi-area power systems. However, its complete relian...
By Ahmad Mohammad Saber, Alok Paranjape, Jehad Jilan, Niranjana Naveen Nambiar, Amr Youssef, Deepa Kundur
arXiv:2606. 03430v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) deployed in energy infrastructure are vulnerable to model theft attacks, which allow adversaries to create evasive traffic offline.
By Maxime Schwarzer, Laurin Holz, Tobias Huerten, Johannes Loevenich, Thies Moehlenhof, Roberto Rigolin F. Lopes, Veit Hagenmeyer