Safeguarding SCADA systems with anomaly detection

Conference paper


Bigham, J., Gamez, D. and Lu, N. 2003. Safeguarding SCADA systems with anomaly detection. Gorodetsky, V., Popyack, L. and Skormin, V. (ed.) Second International Workshop on Mathematical Methods, Models, and Architectures for Computer Network Security. St. Petersburg, Russia 21 - 23 Sep 2003 Berlin, Heidelberg Springer. pp. 171-182 https://doi.org/10.1007/978-3-540-45215-7_14
TypeConference paper
TitleSafeguarding SCADA systems with anomaly detection
AuthorsBigham, J., Gamez, D. and Lu, N.
Abstract

This paper will show how the accuracy and security of SCADA systems can be improved by using anomaly detection to identify bad values caused by attacks and faults. The performance of invariant induction and n- gram anomaly-detectors will be compared and this paper will also outline plans for taking this work further by integrating the output from several anomaly- detecting techniques using Bayesian networks. Although the methods outlined in this paper are illustrated using the data from an electricity network, this research springs from a more general attempt to improve the security and dependability of SCADA systems using anomaly detection.

KeywordsBayesian Network; Anomaly Detection; Electricity Network; Topology Error; SCADA System
ConferenceSecond International Workshop on Mathematical Methods, Models, and Architectures for Computer Network Security
Page range171-182
Proceedings TitleComputer Network Security: Second International Workshop on Mathematical Methods, Models, and Architectures for Computer Network Security, MMM-ACNS 2003, St. Petersburg, Russia, September 21-23, 2003, Proceedings
SeriesLecture Notes in Computer Science
EditorsGorodetsky, V., Popyack, L. and Skormin, V.
ISSN0302-9743
Electronic1611-3349
ISBN
Paperback9783540407973
Electronic9783540452157
PublisherSpringer
Place of publicationBerlin, Heidelberg
Publication dates
Print09 Sep 2003
Online01 Dec 2003
Publication process dates
Deposited21 Sep 2023
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-540-45215-7_14
Web of Science identifierWOS:000187294700014
LanguageEnglish
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