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dc.contributor.author Hirat, K
dc.contributor.author Kudo, T
dc.contributor.author Kimura, T
dc.contributor.author Inoue, Y
dc.contributor.author Aman, H
dc.contributor.editor Fernando, KSD
dc.date.accessioned 2022-11-29T08:30:07Z
dc.date.available 2022-11-29T08:30:07Z
dc.date.issued 2016-12
dc.identifier.citation ****** en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/19619
dc.description.abstract Machine learning techniques have been achieving significant performance improvements in various kinds of tasks, and they are getting applied in many research fields. While we benefit from such techniques in many ways, they can be a serious security threat to the Internet if malicious attackers become able to utilize them to detect software vulnerabilities. This paper introduces a new concept of self-evolving botnets, where computing resources of infected hosts are exploited to discover unknown vulnerabilities in non-infected hosts. We propose a stochastic epidemic model that incorporates such a feature of botnets, and show its behaviors through numerical experiments. en_US
dc.language.iso en en_US
dc.publisher Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka en_US
dc.subject Malware en_US
dc.subject botnet en_US
dc.subject epidemic model en_US
dc.subject vulnerability en_US
dc.subject Markov chain en_US
dc.title Stochastic modeling for self-evolving botnets en_US
dc.identifier.faculty IT en_US
dc.identifier.department Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa. en_US
dc.identifier.year 2016 en_US
dc.identifier.conference International Conference on Information Technology Research 2016 en_US
dc.identifier.place Moratuwa. Sri Lanka en_US
dc.identifier.pgnos pp. 14-17 en_US
dc.identifier.proceeding Proceedings of the International Conference in Information Technology Research 2016 en_US
dc.identifier.email hirata@kansai-u.ac.jp en_US
dc.identifier.email t-kudo@ele.setsunan.ac.jp en_US
dc.identifier.email kimura@ee.kagu.tus.ac.jp en_US
dc.identifier.email y-inoue@post.comm.eng.osaka-u.ac.jp en_US
dc.identifier.email aman@ehime-u.ac.jp en_US


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  • ICITR - 2016 [10]
    International Conference on Information Technology Research (ICITR)

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