Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8568
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dc.contributor.authorSharma, Shivi-
dc.contributor.authorSharma, Ashish-
dc.contributor.authorSaini, Hemraj-
dc.date.accessioned2022-12-13T05:14:24Z-
dc.date.available2022-12-13T05:14:24Z-
dc.date.issued2019-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8568-
dc.description.abstractBig Data has caught the attention of research, science, and business world due to the advancement in digitalization. With the evolution of the Internet of Things (IoT), data is increasing by massive amounts every day. In the big data environment, securing a large amount of data has become a challenging issue in both security and research industry. In this paper, a framework has been proposed to inspect malignant information and suspicious activities traveling over the networks by utilizing Hive Queries. This framework’s procedure loads activity information into Hadoop Distributed File System (HDFS) through a Hive database thus examining the information. This information is sorted as IP Wise, Port Wise, and Protocol Wise. Hive queries will help to achieve these three goals:- 1) Traffic classification 2) Interrupt Identification 3) analyzing of network traffic. Using this framework provides users’ a benefit of being able to investigate Big Data and helps them to detect attacks. Therefore, this framework will allow prevention of network attacks and enable real-time detection in a Big Data environment.en_US
dc.language.isoenen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectBig dataen_US
dc.subjectHadoopen_US
dc.subjectNetwork attacken_US
dc.subjectNetwork security analysisen_US
dc.titleAdvanced Network Security Analysis (ANSA) in Big Data Technologyen_US
dc.typeArticleen_US
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