Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing
Joint Authors
Andrysiak, Tomasz
Saganowski, Łukasz
Kiedrowski, Piotr
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-25
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Information Technology and Computer Science
Abstract EN
One of the basic elements of a Smart City is the urban infrastructure management system, in particular, systems of intelligent street lighting control.
However, for their reliable operation, they require special care for the safety of their critical communication infrastructure.
This article presents solutions for the detection of different kinds of abuses in network traffic of Smart Lighting infrastructure, realized by Power Line Communication technology.
Both the structure of the examined Smart Lighting network and its elements are described.
The article discusses the key security problems which have a direct impact on the correct performance of the Smart Lighting critical infrastructure.
In order to detect an anomaly/attack, we proposed the usage of a statistical model to obtain forecasting intervals.
Then, we calculated the value of the differences between the forecast in the estimated traffic model and its real variability so as to detect abnormal behavior (which may be symptomatic of an abuse attempt).
Due to the possibility of appearance of significant fluctuations in the real network traffic, we proposed a procedure of statistical models update which is based on the criterion of interquartile spacing.
The results obtained during the experiments confirmed the effectiveness of the presented misuse detection method.
American Psychological Association (APA)
Andrysiak, Tomasz& Saganowski, Łukasz& Kiedrowski, Piotr. 2017. Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-19.
https://search.emarefa.net/detail/BIM-1203145
Modern Language Association (MLA)
Andrysiak, Tomasz…[et al.]. Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing. Security and Communication Networks No. 2017 (2017), pp.1-19.
https://search.emarefa.net/detail/BIM-1203145
American Medical Association (AMA)
Andrysiak, Tomasz& Saganowski, Łukasz& Kiedrowski, Piotr. Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-19.
https://search.emarefa.net/detail/BIM-1203145
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203145