Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/9541
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dc.contributor.authorSheth, Kavisha-
dc.date.accessioned2021-01-05T06:12:46Z-
dc.date.available2021-01-05T06:12:46Z-
dc.date.issued2020-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/9541-
dc.description.abstractIn today's world and institution find themselves in complex situation for securing their system and data from increasing vulnerabilities that is why it would be better to discover and identify these vulnerabilities in advance before attacker can exploit them. Thus vulnerability assessment and penetration testing techniques helps it to determine whether the arrangements in securing system are working properly or not by fixing those security gaps. The report consists of two main sections, the first section dealing with existing techniques of vulnerability testing and second section on a new method which employs machine learning techniques for detecting malicious activity like Phishing URL,spam mail and malicious file .en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries18MCEI12;-
dc.subjectComputer 2018en_US
dc.subjectProject Report 2018en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject18MCEIen_US
dc.subject18MCEI12en_US
dc.subjectINSen_US
dc.subjectINS 2018en_US
dc.subjectCE (INS)en_US
dc.titlePenetration Testing using MachineLearningen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE (INS)

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