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Anomaly Detection in Smart Metering Infrastructure with the Use of Time Series Analysis
المؤلفون المشاركون
Andrysiak, Tomasz
Saganowski, Łukasz
Kiedrowski, Piotr
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-07-18
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1187595
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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