FDIAs on hybrid trading Transactive Energy Markets: Attacks, impacts, and prevention

Transactive Energy Market (TEM) operates a day-ahead market for efficient energy management and determines the energy prices in advance for the future period. This predetermined rate is used during real-time energy trading. Hence, it is crucial to provide the correct energy forecast to estimate fair energy prices for all users. However, this market poses a potential opportunity for attackers to manipulate energy prices through False Data Injection Attacks (FDIAs). Moreover, sharing energy forecasts with market operators (MO) or participants violates users’ privacy. To address these issues, this paper first presents two FDIAs to a day-ahead TEM and then numerically evaluates their effects. Then, we design a novel framework to address the trade-off between sharing forecasts and user privacy. We show how users can share the energy forecast with MO and other participants securely while preserving privacy using the developed framework. Finally, we show how our proposed framework detects malicious activities of users (e.g., deviation of actual energy supply/demand from forecast beyond a threshold) and prevent FDIAs effectively.