Integrating historical and real-time anomaly detection to create a more resilient smart grid architecture
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Authors
Drakontaidis, Spencer
Stanchi, Michael
Glazer, Gabriel
Davis, Antoine
Stark, Madison
Clay, Caleb
Hussey, Jason
Barry, Nicholas
Leger, Aaron St.
Matthews, Suzanne J.
Issue Date
2018-04-10
Type
proceedings-article
Language
Keywords
Computer systems organization , Embedded and cyber-physical systems , Hardware , Energy distribution , Security and privacy
Alternative Title
Abstract
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 [2]. In contrast to previous work [3, 4], we explore historical analysis using Apache Spark [5] 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.
Description
Citation
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
Publisher
ACM