Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505474
Title: Multi-objective genetic programming with an application to intrusion detection in computer networks
Author: Badran, Khaled
ISNI:       0000 0004 2677 5330
Awarding Body: The University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2009
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Abstract:
The widespread connectivity of computers all over the world has encouraged intruders to threaten the security of computing systems by targeting the confidentiality and integrity of information, and the availability of systems. Traditional techniques such as user authentication, data encryption and firewalls have been implemented to defend computer security but still have problems and weak points. Therefore the development of intrusion detection systems (EDS) has aroused much research interest with the aim of preventing both internal and external attacks. In misuse-based, network-based IDS, huge history files of computer network usage are analysed hi order to extract useful information, and rules are extracted to judge future network usage as legal or illegal. This process is considered as data mining for intrusion detection in computer networks.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.505474  DOI: Not available
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