Determination of Optimal Cluster Number in Connection to SCADA

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63516901" target="_blank" >RIV/70883521:28140/17:63516901 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-57141-6_15" target="_blank" >http://dx.doi.org/10.1007/978-3-319-57141-6_15</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-57141-6_15" target="_blank" >10.1007/978-3-319-57141-6_15</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Determination of Optimal Cluster Number in Connection to SCADA

Popis výsledku v původním jazyce

The recent evolution of cyber-attacks creates eminent pressure on information and communication systems. The increasing number of cyber-attacks and their sophistication have resulted in needs of the new type of cyber de-fense. The anomaly detection in relation to intrusion detection system (IDS) in connection with standard cyber defense technologies may be the answer to contemporary development in cyber security. Moreover, unsupervised anomaly detection based on K-means algorithm is broadly examined by a considerable number of researchers. Therefore, the algorithm is a solid selection in relation to intrusion detection system. However, one of the problems is to determine a proper number of cluster for the K-means. Nonetheless, there are methods to determine the optimal number of clusters. The aim of the article is to determine the number of clusters in relation to Supervisory Control and Data Acquisition system.

Název v anglickém jazyce

Determination of Optimal Cluster Number in Connection to SCADA

Popis výsledku anglicky

The recent evolution of cyber-attacks creates eminent pressure on information and communication systems. The increasing number of cyber-attacks and their sophistication have resulted in needs of the new type of cyber de-fense. The anomaly detection in relation to intrusion detection system (IDS) in connection with standard cyber defense technologies may be the answer to contemporary development in cyber security. Moreover, unsupervised anomaly detection based on K-means algorithm is broadly examined by a considerable number of researchers. Therefore, the algorithm is a solid selection in relation to intrusion detection system. However, one of the problems is to determine a proper number of cluster for the K-means. Nonetheless, there are methods to determine the optimal number of clusters. The aim of the article is to determine the number of clusters in relation to Supervisory Control and Data Acquisition system.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1303" target="_blank" >LO1303: Podpora udržitelnosti a rozvoje Centra bezpečnostních, informačních a pokročilých technologií (CEBIA-Tech)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

SOFTWARE ENGINEERING TRENDS AND TECHNIQUES IN INTELLIGENT SYSTEMS, CSOC2017, VOL 3 Book Series: Advances in Intelligent Systems and Computing

ISBN

978-3-319-57141-6

ISSN

2194-5357

e-ISSN

neuvedeno

Počet stran výsledku

12

Strana od-do

136-147

Název nakladatele

Springer International Publishing AG

Místo vydání

Cham

Místo konání akce

Zlín

Datum konání akce

26. 4. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000405338500015