Network Intrusion Detection With a Hashing Based Apriori Algorithm Using Hadoop Mapreduce

dc.authorid Misra, Sanjay/0000-0002-3556-9331
dc.authorid Maskeliunas, Rytis/0000-0002-2809-2213
dc.authorid Damaševičius, Robertas/0000-0001-9990-1084
dc.authorid azeez, nureni ayofe/0000-0002-1475-2612
dc.authorscopusid 53864626700
dc.authorscopusid 57212404222
dc.authorscopusid 56962766700
dc.authorscopusid 27467587600
dc.authorscopusid 6603451290
dc.authorwosid Misra, Sanjay/K-2203-2014
dc.authorwosid Maskeliunas, Rytis/J-7173-2017
dc.authorwosid Damaševičius, Robertas/E-1387-2017
dc.authorwosid azeez, nureni ayofe/I-8328-2018
dc.contributor.author Azeez, Nureni Ayofe
dc.contributor.author Ayemobola, Tolulope Jide
dc.contributor.author Misra, Sanjay
dc.contributor.author Maskeliunas, Rytis
dc.contributor.author Damasevicius, Robertas
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T15:41:37Z
dc.date.available 2024-07-05T15:41:37Z
dc.date.issued 2019
dc.department Atılım University en_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, Poland en_US
dc.description Misra, Sanjay/0000-0002-3556-9331; Maskeliunas, Rytis/0000-0002-2809-2213; Damaševičius, Robertas/0000-0001-9990-1084; azeez, nureni ayofe/0000-0002-1475-2612 en_US
dc.description.abstract Ubiquitous 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.sponsorship H2020 LEIT Information and Communication Technologies [830892] en_US
dc.description.sponsorship This research was funded by H2020 LEIT Information and Communication Technologies, grant number 830892. en_US
dc.identifier.citationcount 22
dc.identifier.doi 10.3390/computers8040086
dc.identifier.issn 2073-431X
dc.identifier.issue 4 en_US
dc.identifier.scopus 2-s2.0-85076591140
dc.identifier.uri https://doi.org/10.3390/computers8040086
dc.identifier.uri https://hdl.handle.net/20.500.14411/3457
dc.identifier.volume 8 en_US
dc.identifier.wos WOS:000505731900021
dc.institutionauthor Mısra, Sanjay
dc.language.iso en en_US
dc.publisher Mdpi en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 39
dc.subject association rule mining en_US
dc.subject intrusion detection en_US
dc.subject cyberattack en_US
dc.subject network security en_US
dc.subject apriori en_US
dc.subject MapReduce en_US
dc.title Network Intrusion Detection With a Hashing Based Apriori Algorithm Using Hadoop Mapreduce en_US
dc.type Article en_US
dc.wos.citedbyCount 24
dspace.entity.type Publication
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