Network Intrusion Detection with a Hashing Based Apriori Algorithm Using Hadoop MapReduce

dc.authoridMisra, Sanjay/0000-0002-3556-9331
dc.authoridMaskeliunas, Rytis/0000-0002-2809-2213
dc.authoridDamaševičius, Robertas/0000-0001-9990-1084
dc.authoridazeez, nureni ayofe/0000-0002-1475-2612
dc.authorscopusid53864626700
dc.authorscopusid57212404222
dc.authorscopusid56962766700
dc.authorscopusid27467587600
dc.authorscopusid6603451290
dc.authorwosidMisra, Sanjay/K-2203-2014
dc.authorwosidMaskeliunas, Rytis/J-7173-2017
dc.authorwosidDamaševičius, Robertas/E-1387-2017
dc.authorwosidazeez, nureni ayofe/I-8328-2018
dc.contributor.authorMısra, Sanjay
dc.contributor.authorAyemobola, Tolulope Jide
dc.contributor.authorMisra, Sanjay
dc.contributor.authorMaskeliunas, Rytis
dc.contributor.authorDamasevicius, Robertas
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-07-05T15:41:37Z
dc.date.available2024-07-05T15:41:37Z
dc.date.issued2019
dc.departmentAtılım Universityen_US
dc.department-temp[Azeez, Nureni Ayofe; Ayemobola, Tolulope Jide] Univ Lagos, Dept Comp Sci, Lagos 100213, Nigeria; [Misra, Sanjay] Covenant Univ, Dept Elect & Informat Engn, Ota 112233, Nigeria; [Misra, Sanjay] Atilim Univ, Dept Comp Engn, TR-06830 Ankara, Turkey; [Maskeliunas, Rytis; Damasevicius, Robertas] Silesian Tech Univ, Fac Appl Math, PL-44100 Gliwice, Polanden_US
dc.descriptionMisra, Sanjay/0000-0002-3556-9331; Maskeliunas, Rytis/0000-0002-2809-2213; Damaševičius, Robertas/0000-0001-9990-1084; azeez, nureni ayofe/0000-0002-1475-2612en_US
dc.description.abstractUbiquitous nature of Internet services across the globe has undoubtedly expanded the strategies and operational mode being used by cybercriminals to perpetrate their unlawful activities through intrusion on various networks. Network intrusion has led to many global financial loses and privacy problems for Internet users across the globe. In order to safeguard the network and to prevent Internet users from being the regular victims of cyber-criminal activities, new solutions are needed. This research proposes solution for intrusion detection by using the improved hashing-based Apriori algorithm implemented on Hadoop MapReduce framework; capable of using association rules in mining algorithm for identifying and detecting network intrusions. We used the KDD dataset to evaluate the effectiveness and reliability of the solution. Our results obtained show that this approach provides a reliable and effective means of detecting network intrusion.en_US
dc.description.sponsorshipH2020 LEIT Information and Communication Technologies [830892]en_US
dc.description.sponsorshipThis research was funded by H2020 LEIT Information and Communication Technologies, grant number 830892.en_US
dc.identifier.citation22
dc.identifier.doi10.3390/computers8040086
dc.identifier.issn2073-431X
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85076591140
dc.identifier.urihttps://doi.org/10.3390/computers8040086
dc.identifier.urihttps://hdl.handle.net/20.500.14411/3457
dc.identifier.volume8en_US
dc.identifier.wosWOS:000505731900021
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectassociation rule miningen_US
dc.subjectintrusion detectionen_US
dc.subjectcyberattacken_US
dc.subjectnetwork securityen_US
dc.subjectapriorien_US
dc.subjectMapReduceen_US
dc.titleNetwork Intrusion Detection with a Hashing Based Apriori Algorithm Using Hadoop MapReduceen_US
dc.typeArticleen_US
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery53e88841-fdb7-484f-9e08-efa4e6d1a090
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