In this paper, we investigate an edge-based approach for the detection and localization of coordinated oscillatory load attacks initiated by exploited EV charging stations against the power grid. We rely on the behavioral characteristics of the power grid in the presence of interconnected EVCS while combining cyber and physical layer features to implement deep learning algorithms for the effective detection of oscillatory load attacks at the EVCS. We evaluate the proposed detection approach by building a real-time test bed to synthesize benign and malicious data, which was generated by analyzing real-life EV charging data collected during recent years. The results demonstrate the effectiveness of the implemented approach with the Convolutional Long-Short Term Memory model producing optimal classification accuracy (99.4\%). Moreover, our analysis results shed light on the impact of such detection mechanisms towards building resiliency into different levels of the EV charging ecosystem while allowing power grid operators to localize attacks and take further mitigation measures. Specifically, we managed to decentralize the detection mechanism of oscillatory load attacks and create an effective alternative for operator-centric mechanisms to mitigate multi-operator and MitM oscillatory load attacks against the power grid. Finally, we leverage the created test bed to evaluate a distributed mitigation technique, which can be deployed on public/private charging stations to average out the impact of oscillatory load attacks while allowing the power system to recover smoothly within 1 second with minimal overhead.

翻译：本文研究了一种基于边缘的方法，用于检测和定位由受攻击的电动汽车充电站（EVCS）针对电网发起的协同振荡负载攻击。我们利用电网在互联EVCS存在下的行为特征，结合网络层和物理层特征以实现深度学习算法，从而在EVCS层面有效检测振荡负载攻击。通过搭建实时测试平台，合成由近年收集的真实电动汽车充电数据生成的良性及恶意数据，对所提检测方法进行了评估。结果表明，该方法效果显著，其中卷积长短期记忆（ConvLSTM）模型实现了最优分类准确率（99.4%）。此外，分析结果揭示了此类检测机制在提升电动汽车充电生态系统各层级韧性中的作用，同时使电网运营商能够定位攻击并采取进一步缓解措施。具体而言，我们成功实现了振荡负载攻击检测机制的去中心化，为运营商中心化机制提供了有效替代方案，以缓解针对电网的多运营商及中间人（MitM）振荡负载攻击。最后，我们利用所建测试平台评估了一种分布式缓解技术，该技术可部署于公共/私人充电站，在最小化开销的同时平均振荡负载攻击的影响，使电力系统在1秒内平稳恢复。