%0 Conference Proceedings
%T Netflow-Based Malware Detection and Data Visualisation System
%+ UTP University of Science and Technology
%A Kozik, Rafał
%A Młodzikowski, Robert
%A Choraś, Michał
%Z Part 7: Various Aspects of Computer Security
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Bialystok, Poland
%Y Khalid Saeed
%Y Władysław Homenda
%Y Rituparna Chaki
%I Springer International Publishing
%3 Computer Information Systems and Industrial Management
%V LNCS-10244
%P 652-660
%8 2017-06-16
%D 2017
%R 10.1007/978-3-319-59105-6_56
%K Cyber security
%K Anomaly detection
%K Botnet
%K NetFlow
%K Visualisation
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X This paper presents a system for network traffic visualisation and anomalies detection by means of data mining and machine learning techniques. First, this work describes and analyses existing solutions in the field of network anomalies detection in order to identify adapted techniques in that area. Afterwards, the system architecture and the adapted tools and libraries are presented. Particularly, two different anomalies detection methods are proposed.The key experiments and analysis focus on performance evaluation of the proposed algorithms. In particular, different setups are considered in order to evaluate such aspects as detection effectiveness and computational complexity.The obtained results are promising and show that the proposed system can be considered as a useful tool for the network administrator.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01656262/document
%2 https://inria.hal.science/hal-01656262/file/448933_1_En_56_Chapter.pdf
%L hal-01656262
%U https://inria.hal.science/hal-01656262
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-10244