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Anomaly Detection in Smart Metering Infrastructure with the Use of Time Series Analysis
Joint Authors
Andrysiak, Tomasz
Saganowski, Łukasz
Kiedrowski, Piotr
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-18
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The article presents solutions to anomaly detection in network traffic for critical smart metering infrastructure, realized with the use of radio sensory network.
The structure of the examined smart meter network and the key security aspects which have influence on the correct performance of an advanced metering infrastructure (possibility of passive and active cyberattacks) are described.
An effective and quick anomaly detection method is proposed.
At its initial stage, Cook’s distance was used for detection and elimination of outlier observations.
So prepared data was used to estimate standard statistical models based on exponential smoothing, that is, Brown’s, Holt’s, and Winters’ models.
To estimate possible fluctuations in forecasts of the implemented models, properly parameterized Bollinger Bands was used.
Next, statistical relations between the estimated traffic model and its real variability were examined to detect abnormal behavior, which could indicate a cyberattack attempt.
An update procedure of standard models in case there were significant real network traffic fluctuations was also proposed.
The choice of optimal parameter values of statistical models was realized as forecast error minimization.
The results confirmed efficiency of the presented method and accuracy of choice of the proper statistical model for the analyzed time series.
American Psychological Association (APA)
Andrysiak, Tomasz& Saganowski, Łukasz& Kiedrowski, Piotr. 2017. Anomaly Detection in Smart Metering Infrastructure with the Use of Time Series Analysis. Journal of Sensors،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1187595
Modern Language Association (MLA)
Andrysiak, Tomasz…[et al.]. Anomaly Detection in Smart Metering Infrastructure with the Use of Time Series Analysis. Journal of Sensors No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1187595
American Medical Association (AMA)
Andrysiak, Tomasz& Saganowski, Łukasz& Kiedrowski, Piotr. Anomaly Detection in Smart Metering Infrastructure with the Use of Time Series Analysis. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1187595
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187595