DocumentCode
2119946
Title
Analysing Behaviours for Intrusion Detection
Author
Mamalakis, George ; Diou, Christos ; Symeonidis, Andreas L.
Author_Institution
School of Electrical and Computer Engineering, Aristotle Univ. of Thessaloniki, Greece
fYear
2015
fDate
8-12 June 2015
Firstpage
2645
Lastpage
2651
Abstract
In this work, a Behaviour-based Intrusion Detection Model is suggested. The proposed model can be employed from a single host configuration to a distributed mixture of host-based and network-based Intrusion Detection Systems (IDSs). Unlike most state-of-the-art IDSs that rely on analysing lower-level, raw-data representations, our proposed architecture suggests to use higher-level notions -behaviours- instead; this way, the IDS is able to identify more sophisticated attacks. To assess our premise, a Behaviour-based IDS (BIDS) prototype has been designed and developed that scans file system data to identify attacks. BIDS achieves high detection rates with low corresponding false positive rates, superseding other state-of-the-art file system IDSs.
Keywords
Clustering algorithms; Computers; Engines; Feature extraction; Generators; Internet of things; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Workshop (ICCW), 2015 IEEE International Conference on
Conference_Location
London, United Kingdom
Type
conf
DOI
10.1109/ICCW.2015.7247578
Filename
7247578
Link To Document