Evaluation of Data Preprocessing Techniques for Anomaly Detection Systems in Industrial Control System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63523743" target="_blank" >RIV/70883521:28140/19:63523743 - isvavai.cz</a>
Result on the web
<a href="https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2019/101.pdf" target="_blank" >https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2019/101.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2507/30th.daaam.proceedings.101" target="_blank" >10.2507/30th.daaam.proceedings.101</a>
Alternative languages
Result language
angličtina
Original language name
Evaluation of Data Preprocessing Techniques for Anomaly Detection Systems in Industrial Control System
Original language description
The critical infrastructure can be defined as main cornerstone of modern society. Therefore, the cyber protection of critical systems like industrial control systems is vital for every modern state. However, conventional techniques are often ineffective to protect these systems. Thus, machine learning is an exceptional way to ensure cyber security in the case of critical infrastructure. The machine learning can process high dimension datasets with thousands of record in real-time. However, these datasets have to be in a proper format. The data preprocessing is a crucial stage in machine learning and can negatively influence final results. We introduce a comprehensive comparison of the main data preprocessing techniques in the relation of the network anomaly detection system. Moreover, the preprocessing of continuous datasets is considered as the subject of the research The neural network autoencoder is considered as an anomaly detection algorithm which is used to evaluate proposed solutions.
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
<a href="/en/project/VI20172019054" target="_blank" >VI20172019054: An analitical software module for the real-time resilience evaluation from point of the converged security</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Annals of DAAAM and Proceedings of the International DAAAM Symposium
ISBN
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ISSN
17269679
e-ISSN
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Number of pages
8
Pages from-to
738-745
Publisher name
Danube Adria Association for Automation and Manufacturing ( DAAAM )
Place of publication
Vídeň
Event location
Zadar
Event date
Oct 23, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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