Anomaly Detection System Based on Classifier Fusion in ICS Environment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63516931" target="_blank" >RIV/70883521:28140/17:63516931 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Anomaly Detection System Based on Classifier Fusion in ICS Environment
Original language description
The detection of cyber-attacks has become a crucial task for highly sophisticated systems like industrial control systems (ICS). These systems are an essential part of critical information infrastructure. Therefore, we can highlight their vital role in contemporary society. The effective and reliable ICS cyber defense is a significant challenge for the cyber security community. Thus, intrusion detection is one of the demanding tasks for the cyber security researchers. In this article, we examine classification problem. The proposed detection system is based on supervised anomaly detection techniques. Moreover, we utilized classifiers algorithms in order to increase intrusion detection capabilities. The fusion of the classifiers is the way how to achieve the predefined goal.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings 2017 International Conference on Soft Computing, Intelligent System and Information Technology
ISBN
978-1-4673-9899-2
ISSN
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e-ISSN
neuvedeno
Number of pages
7
Pages from-to
32-38
Publisher name
IEEE Computer Society Conference Publishing Services (CPS)
Place of publication
Washington, DC
Event location
Denpasar, Bali
Event date
Sep 26, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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