Integrating historical and real-time anomaly detection to create a more resilient smart grid architecture
Ensuring the security of the power grid is critical for national interests and necessitates new ways to detect power anomalies and respond to potential failures. In this poster, we describe our efforts to develop and optimize analysis methodologies for a 1000 : 1 scale emulated smart grid at the United States Military Academy . In contrast to previous work [3, 4], we explore historical analysis using Apache Spark  and integrate a Raspberry Pi into our testbed for real-time anomaly detection. We also implement a software controlled physical event and fault generator to induce and measure faults. Figure 1 gives an overview of our system.
Computer systems organization, Embedded and cyber-physical systems, Hardware, Energy distribution, Security and privacy
Spencer Drakontaidis, Michael Stanchi, Gabriel Glazer, Antoine Davis, Madison Stark, Caleb Clay, Jason Hussey, Nicholas Barry, Aaron St. Leger, and Suzanne J. Matthews. 2018. Integrating historical and real-time anomaly detection to create a more resilient smart grid architecture: poster. In Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security (HoTSoS '18). Association for Computing Machinery, New York, NY, USA, Article 22, 1. https://doi.org/10.1145/3190619.3191683