Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.722080
Title: Distributed monitoring for intrusion detection in clouds
Author: Alshamrani, S. S.
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
This thesis is in the field of Computer Science. More precisely, its main research themes are in the applied part of the field Cloud Computing. The main focus in this work is on monitoring of cloud systems in a distributed fashion. This work is a natural continuation of previous studies on discovering the symptoms malicious behaviours in cloud systems. Our line of research is based on efficient discovery of the symptoms of threats. This challenge is met through the design and analysis of new algorithms carrying out this job. Several algorithms are studied. First, a simplified version of previously studied Mobility algorithm is proposed. The new algorithm is named Reduce-Max algorithm. This algorithm is analysed on eight different data sets. Then two modifications of Reduce-Max algorithm are considered. The first one is called Randomised-Local Reduction and the second one is Deterministic-Centralised Reduction. Further, the algorithms are tested under different models of symptoms appearance. The work continues with studies of Reduce-Max and its two modifications in hierarchical systems, which concludes in the design of a new algorithm, called Random-Start-Round-Robin. Finally, this thesis concludes with work on balancing Mobility Algorithm. An integral part of my PhD work are experiments of proposed algorithms where the emphasis is on proper modeling of monitoring of cloud systems. Further discussion is based on the results of these experiments reflected in the final conclusions.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.722080  DOI: Not available
Share: