arXiv (All)
open access
False Data Injection Attack on Electric Vehicle-Assisted Voltage Regulation
With the large scale penetration of electric vehicles (EVs) and the advent of bidirectional chargers, EV aggregators will become a major player in the voltage regulation market. This paper proposes a novel false data injection attack (FDIA) against the voltage regulation capacity estimation of EV ch
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Detection of False-Data Injection and Replay Attacks on Controllable Crypto-Mining Loads in High-Penetration Renewable Microgrids#235447
- A novel hybrid cybersecurity scheme against false data injection attacks in automated power systems#672090
- Synthetic false data injection-inspired perturbation framework for power grid attack detection using graph neural networks and deep learning models#1169163
- A Model-Independent Trojan Attack on Deep Learning-Based FDIA Detection in Smart Grid Protection Systems.#489725
- Learning Without Adversarial Training: A Physics-Informed Neural Network for Secure Power System State Estimation under False Data Injection Attacks#974394
Record · ID 1469085
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive