Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/220091
Title: A Mathematical Model for Prediction of Infectious Virtual Machines in IaaS Cloud Environment
Researcher: Dash, Satyabrata
Guide(s): Mishra, Ashok
Keywords: Engineering and Technology
University: Centurion University of Technology and Management
Completed Date: 03/03/2018
Abstract: This work describes a new model to predict newlinethe trustworthiness of the IaaS virtual platform. This newlineframework also deals with threats and predicts the newlinegrowth rate of vulnerable virtual machines in the newlinecloud environment irrespective of the user s newlineapplications and security policy. It will basically newlineensure the degree of the security of virtual machines newlinein a cloud environment which would help the cloud newlineservice providers to take the quick decisions about the newlineup gradation of the counter attack measurements. newlineIt mainly outlines about three contributions. The first newlineone explains about a mathematical ontology based newlineupon different types of vulnerable virtual machines in newlineIaaS virtual platforms. T he second one explores the newlinebehaviour of Infectious Virtual Machines using newlinePredator-Prey model based on Lakota-Volterra newlineEquations. The final one is the dynamics of Exposed newlineVirtual Machine (EVM) and Infectious Virtual newlineMachine (IVM) in the cloud environment newline
Pagination: 4.48 mb, 102 pg
URI: http://hdl.handle.net/10603/220091
Appears in Departments:Computer Sc. and Enggineering

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final thesis _satyabrata dash.pdf2 MBAdobe PDFView/Open
firstpage_satyabrata.pdf143.65 kBAdobe PDFView/Open
preface_satyabrata.pdf228 kBAdobe PDFView/Open


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