arXiv:2605. 28912v2 Announce Type: replace Abstract: The rapid growth of AI-driven data centers and large-scale energy storage systems is increasing the reliance of power system operation on real-time measurement data and automated decision-making.
By Xin Li, Chenhan Xiao, Jonathan Cohen, Aviad Elyashar, Yang Weng, Rami Puzis
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.
By Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang, Jinyuan Sun, Kevin Tomsovic
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:2607. 06647v1 Announce Type: cross Abstract: Open Radio Access Networks (O-RAN) increasingly delegate near-real-time control to deep reinforcement learning (DRL) xApps obtained from third-party vendors, creating a new supply-chain attack surface.
By Md Raihan Uddin, Fatemeh Lotfi, Tolunay Seyfi, Fatemeh Afghah
arXiv:2607. 16031v1 Announce Type: cross Abstract: Data-driven pre-fault dynamic security assessment (DSA) rapidly evaluates the dynamic risk of credible contingencies on a power system using machine learning.
By Olayiwola Arowolo, Maosheng Yang, Jochen Cremer