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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Bigham, J., Gamez, D., & Lu, N. (2003). Safeguarding SCADA systems with anomaly detection. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2776, 171–182. https://doi.org/10.1007/978-3-540-45215-7_14
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