SYCESYMar 19

Deceiving Flexibility: A Stealthy False Data Injection Model in Vehicle-to-Grid Coordination

arXiv:2603.184242.1h-index: 6
Predicted impact top 94% in SY · last 90 daysOriginality Incremental advance
AI Analysis

This addresses a cybersecurity vulnerability in aggregated V2G systems, which is an incremental but important concern for grid operators and electric vehicle users.

This paper tackles the problem of stealthy false data injection attacks in Vehicle-to-Grid coordination, showing that manipulating reported State of Charge and power measurements from a subset of electric vehicles can deceive operators and deteriorate grid frequency stability without direct control access.

Electric vehicles (EVs) in Vehicle-to-Grid (V2G) systems act as distributed energy resources that support grid stability. Centralized coordination such as the extended State Space Model (eSSM) enhances scalability and estimation efficiency but may introduce new cyber-attack surfaces. This paper presents a stealthy False Data Injection Attack (FDIA) targeting eSSM-based V2G coordination. Unlike prior studies that assume attackers can disrupt physical charging or discharging processes, we consider an adversary who compromises only a subset of EVs, and limiting their influence to the manipulation of reported State of Charge (SoC) and power measurements. By doing so, the attacker can deceive the operator's perception of fleet flexibility while remaining consistent with model-based expectations, thus evading anomaly detection. Numerical simulations show that the proposed stealthy FDIA can deteriorate grid frequency stability even without direct access to control infrastructure. These findings highlight the need for enhanced detection and mitigation mechanisms tailored to aggregated V2G frameworks

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes