Network User Behaviour Analysis by Machine Learning Methods

Received: 20 June 2021 Revised: 10 Aug 2021 Online: 07 Sep 2021 KEYWORDS: cybersecurity, web users analysis, machine learning, clustering algorithm, web page categorisation Creative Commons BY-NC 4.0 Introduction Today's world and our society heavily depend on communication. Without a massive i...

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Bibliographic Details
Published in:Information & security 2021, Vol.50 (1), p.66-78
Main Author: Turčaník, Michal
Format: Article
Language:English
Subjects:
Algorithms
Clustering
Communication
Cybersecurity
Data encryption
Data mining
Information sources
Machine learning
Peer to peer computing
User behavior
Online Access:Get full text
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Summary:Received: 20 June 2021 Revised: 10 Aug 2021 Online: 07 Sep 2021 KEYWORDS: cybersecurity, web users analysis, machine learning, clustering algorithm, web page categorisation Creative Commons BY-NC 4.0 Introduction Today's world and our society heavily depend on communication. Without a massive investment in time or money, we can find many ways and schemes to attack a communication infrastructure,3 an operating system and an application.4 From a military point of view, coordinated cyberattacks against friendly units during operations are very dangerous. [...]we must achieve a high-security level for communication networks to successfully fulfil the tasks of military and non-military operations. Mining of web user behaviour and patterns from the log files saved on the route of packets from source to destination has been an attractive field for research and also for business applications. Data mining approaches can be applied to automatically dig information with the goal to find out some habits and tendencies.9,10,11 In that case, the web access log file is analysed in order to divide users on the basis of a selected algorithm into several clusters.
ISSN:0861-5160
1314-2119
DOI:10.11610/isij.5014