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dc.contributor.authorDash, W
dc.contributor.authorCraven, MJ
dc.contributor.editorLivraga G
dc.contributor.editorMitchell CJ
dc.date.accessioned2017-09-16T11:19:54Z
dc.date.available2017-09-16T11:19:54Z
dc.date.issued2017-09-14
dc.identifier.isbn9783319680620
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/10026.1/9938
dc.description.abstract

A botnet is a program designed to perform a specific task using multiple computers connected in a network. In this paper we will focus on botnets being used to distribute malicious programs. In the real world, botnets have been shown to exhibit more aggressive and sophisticated behaviour than traditional malware. Botnets are used to infect computer networks and hence their success depends on the properties of the networks. We observe the behaviour of mathematical models used to describe botnets when botnet parameters are varied to understand if such variation is beneficial to their spread. We also introduce novel models for depicting botnet behaviour using master equations. These models, unlike previous ones, address nodes of distinct categories in a network as a sequence of probability distributions rather than a value at each time interval. We also contribute visualisations for these models. This paper is a substantial expansion of unpublished work the first author performed while on a Nuffield student research placement, with the second author the project supervisor.

dc.format.extent72-88
dc.language.isoen
dc.publisherSpringer International Publishing
dc.subjectBotnet
dc.subjectDifferential equation
dc.subjectMaster equation
dc.subjectVisualisation
dc.subjectComplex systems security
dc.subjectSecurity in P2P (peer to peer) systems
dc.titleExploring Botnet Evolution via Multidimensional Models and Visualisation
dc.typeconference
dc.typeProceedings Paper
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000463256600005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.date-start2017-09-14
plymouth.date-finish2017-09-15
plymouth.volumeLecture Notes in Computer Science 10547
plymouth.publisher-urlhttp://dx.doi.org/10.1007/978-3-319-68063-7_5
plymouth.conference-nameSTM 2017
plymouth.publication-statusPublished
plymouth.journal1611-3349
dc.identifier.doi10.1007/978-3-319-68063-7_5
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/EXTENDED UoA 10 - Mathematical Sciences
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA10 Mathematical Sciences
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.publisher.placeOslo, Norway
dcterms.dateAccepted2017-08-02
dc.identifier.eissn1611-3349
dc.rights.embargoperiodNo embargo
rioxxterms.versionofrecord10.1007/978-3-319-68063-7_5
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2017-09-14
rioxxterms.typeConference Paper/Proceeding/Abstract


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