Autonomous malicious activity inspector - AMAI

Manzoor, Umar, Nefti, Samia and Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 2010. Autonomous malicious activity inspector - AMAI. Presented at: NLDB 2010: International Conference on Application of Natural Language to Information Systems, Cardiff, UK, 23-25 June 2010. Natural Language Processing and Information Systems. Lecture Notes in Computer Science. Lecture Notes in Computer Science (6177) Berlin: Springer Verlag, pp. 204-215. 10.1007/978-3-642-13881-2_21

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Abstract

Computer networks today are far more complex and managing such networks is not more then a job of an expert. Monitoring systems helps network administrator in monitoring and protecting the network by not allowing the users to run illegal application or changing the configuration of the network node. In this paper, we have proposed Autonomous Malicious Activity Inspector – AMAI which uses ontology based knowledge base to predict unknown illegal applications based on known illegal application behaviors. AMAI is an Intelligent Multi Agent System used to detect known and unknown malicious activities carried out by the users over the network. We have compared ABSAMN and AMAI concurrently at the university campus having seven labs equipped with 20 to 300 number of PCs in various labs; results shows AMAI outperform ABSAMN in every aspect.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Publisher:	Springer Verlag
ISBN:	9783642138805
ISSN:	0302-9743
Last Modified:	20 Oct 2022 08:08
URI:	https://orca.cardiff.ac.uk/id/eprint/27328

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