U.S. Department of EnergyOffice of Scientific and Technical Information
Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid
Abstract
As an increasing number of devices in the power-grid rely on high-precision clocks to measure electrical properties and time stamp data, GPS receivers have become a vulnerability on the power-grid. GPS spoofing attacks, in which a fake signal is transmitted, can cause sensor measurement errors that can misinform protective equipment and grid operators for both the transmission and distribution grid. The technology being developed to secure precision clocks in the transmission grid are not appropriate for the distribution grid. Thus, there is a need to developed anomaly detection algorithms that are suitable for the hardware available on the distribution grid. Traditionally, a distributed detection framework is comprised of spatially distributed nodes which acquire observations about a quantity of interest and sends the data to the fusion center, where a global decision is made. Instead the distribution grid has low-power devices, such as smart inverters and microPMUs, that could be used to perform highly parallelized calculations. Having on node calculations is beneficial since it is more network and computation efficient, as the more calculations can be performed where the data is being captured instead of communicating across a slow network to a centralized fusion center. Instead, we could employ an alternatemore »
- Authors:
-
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1490934
- Report Number(s):
- LLNL-TR-763473
953248
- DOE Contract Number:
- AC52-07NA27344
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Fox, A., Ponce, C., Applegate, A., Nygaard, M., and Duan, N. Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid. United States: N. p., 2018.
Web. doi:10.2172/1490934.
Fox, A., Ponce, C., Applegate, A., Nygaard, M., & Duan, N. Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid. United States. https://doi.org/10.2172/1490934
Fox, A., Ponce, C., Applegate, A., Nygaard, M., and Duan, N. 2018.
"Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid". United States. https://doi.org/10.2172/1490934. https://www.osti.gov/servlets/purl/1490934.
@article{osti_1490934,
title = {Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid},
author = {Fox, A. and Ponce, C. and Applegate, A. and Nygaard, M. and Duan, N.},
abstractNote = {As an increasing number of devices in the power-grid rely on high-precision clocks to measure electrical properties and time stamp data, GPS receivers have become a vulnerability on the power-grid. GPS spoofing attacks, in which a fake signal is transmitted, can cause sensor measurement errors that can misinform protective equipment and grid operators for both the transmission and distribution grid. The technology being developed to secure precision clocks in the transmission grid are not appropriate for the distribution grid. Thus, there is a need to developed anomaly detection algorithms that are suitable for the hardware available on the distribution grid. Traditionally, a distributed detection framework is comprised of spatially distributed nodes which acquire observations about a quantity of interest and sends the data to the fusion center, where a global decision is made. Instead the distribution grid has low-power devices, such as smart inverters and microPMUs, that could be used to perform highly parallelized calculations. Having on node calculations is beneficial since it is more network and computation efficient, as the more calculations can be performed where the data is being captured instead of communicating across a slow network to a centralized fusion center. Instead, we could employ an alternate peer-to-peer type of information exchange on the distribution grid that can still reach a global decision. A decentralized approach to anomaly detection makes efficient use of the computational and network bandwidth that exists, and it also lacks the single point of failure of a centralized approach. Thus, a decentralized local information exchange and/or inference is preferred. Lastly, the unreliability of the distribution grid network connections and potential noise or error in the measurements must be considered. In order to produce an effective detection tool, a Byzantine-fault tolerant and asynchronous algorithm must be developed. Thus, the first phase of our project is to develop a distributed, decentralized, asynchronous, Byzantine-fault tolerant, collaborative autonomy-based anomaly detection algorithm to collectively analyze clusters of data for signs of a malicious attack.},
doi = {10.2172/1490934},
url = {https://www.osti.gov/biblio/1490934},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Nov 03 00:00:00 EDT 2018},
month = {Sat Nov 03 00:00:00 EDT 2018}
}