PCA-based method for detecting integrity attacks on advanced metering infrastructure

Varun Badrinath Krishna, Gabriel A. Weaver, William H. Sanders

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Electric utilities are in the process of installing millions of smart meters around the world, to help improve their power delivery service. Although many of these meters come equipped with encrypted communications, they may potentially be vulnerable to cyber intrusion attempts. These attempts may be aimed at stealing electricity, or destabilizing the electricity market system. Therefore, there is a need for an additional layer of verification to detect these intrusion attempts. In this paper, we propose an anomaly detection method that uniquely combines Principal Component Analysis (PCA) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to verify the integrity of the smart meter measurements. Anomalies are deviations from the normal electricity consumption behavior. This behavior is modeled using a large, open database of smart meter readings obtained from a real deployment. We provide quantitative arguments that describe design choices for this method and use false-data injections to quantitatively compare this method with another method described in related work.

Original languageEnglish (US)
Title of host publicationQuantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings
EditorsJavier Campos, Boudewijn R. Haverkort
PublisherSpringer-Verlag
Pages70-85
Number of pages16
ISBN (Print)9783319222639
DOIs
StatePublished - Jan 1 2015
Event12th International Conference on Quantitative Evaluation of Systems, QEST 2015 - Madrid, Spain
Duration: Sep 1 2015Sep 3 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9259
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Quantitative Evaluation of Systems, QEST 2015
CountrySpain
CityMadrid
Period9/1/159/3/15

Fingerprint

Advanced metering infrastructures
Smart meters
Principal component analysis
Integrity
Principal Component Analysis
Infrastructure
Attack
Electricity
Electric utilities
Spatial Clustering
Electricity Market
Anomaly Detection
Anomaly
Injection
Deviation
Communication
Verify

Keywords

  • AMI
  • Analysis
  • Anomaly
  • Communication
  • Component
  • Computer
  • Cyber-physical
  • Data
  • Detection
  • Electricity
  • Energy
  • Grid
  • Meter
  • Network
  • PCA
  • Principal
  • SVD ·DBSCAN
  • Security
  • Smart
  • Theft

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Krishna, V. B., Weaver, G. A., & Sanders, W. H. (2015). PCA-based method for detecting integrity attacks on advanced metering infrastructure. In J. Campos, & B. R. Haverkort (Eds.), Quantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings (pp. 70-85). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9259). Springer-Verlag. https://doi.org/10.1007/978-3-319-22264-6_5

PCA-based method for detecting integrity attacks on advanced metering infrastructure. / Krishna, Varun Badrinath; Weaver, Gabriel A.; Sanders, William H.

Quantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings. ed. / Javier Campos; Boudewijn R. Haverkort. Springer-Verlag, 2015. p. 70-85 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9259).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Krishna, VB, Weaver, GA & Sanders, WH 2015, PCA-based method for detecting integrity attacks on advanced metering infrastructure. in J Campos & BR Haverkort (eds), Quantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9259, Springer-Verlag, pp. 70-85, 12th International Conference on Quantitative Evaluation of Systems, QEST 2015, Madrid, Spain, 9/1/15. https://doi.org/10.1007/978-3-319-22264-6_5
Krishna VB, Weaver GA, Sanders WH. PCA-based method for detecting integrity attacks on advanced metering infrastructure. In Campos J, Haverkort BR, editors, Quantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings. Springer-Verlag. 2015. p. 70-85. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-22264-6_5
Krishna, Varun Badrinath ; Weaver, Gabriel A. ; Sanders, William H. / PCA-based method for detecting integrity attacks on advanced metering infrastructure. Quantitative Evaluation of Systems - 12th International Conference, QEST 2015, Proceedings. editor / Javier Campos ; Boudewijn R. Haverkort. Springer-Verlag, 2015. pp. 70-85 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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