Publication:
A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network

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dc.citedby3
dc.contributor.authorRidwan M.A.en_US
dc.contributor.authorRadzi N.A.M.en_US
dc.contributor.authorAzmi K.H.M.en_US
dc.contributor.authorAbdullah F.en_US
dc.contributor.authorAhmad W.S.H.M.W.en_US
dc.contributor.authorid57193648099en_US
dc.contributor.authorid57218936786en_US
dc.contributor.authorid57982272200en_US
dc.contributor.authorid56613644500en_US
dc.contributor.authorid58032416800en_US
dc.date.accessioned2024-10-14T03:22:07Z
dc.date.available2024-10-14T03:22:07Z
dc.date.issued2023
dc.description.abstractMachine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. The current Multiprotocol Label Switching (MPLS)-based communication system is packed with exponentially increasing applications and different Quality-of-Services (QoS) requirements. As the network is getting complex and congested, it will become challenging to satisfy the QoS requirements in the MPLS network. This study proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). The datasets are then fed into MATLAB to train ML classifiers and regression models to classify the incoming traffic as normal or attack and predict traffic delays for all available routes, respectively. Only the normal traffic predicted by the ML-IDS algorithm will be allowed to enter the network domain, and the route with the fastest delay predicted by the ML-RA is assigned for routing. The ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). From the performance evaluations, the ML-RA shows 100 percent accuracy in predicting the fastest route in the network. During network congestion, the proposed ML outperforms the RIPv2 in terms of delay and throughput on average by 57.61 percent and 46.57 percent, respectively. � 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.14569/IJACSA.2023.0140412
dc.identifier.epage107
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85158159199
dc.identifier.spage94
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85158159199&doi=10.14569%2fIJACSA.2023.0140412&partnerID=40&md5=66fc3752bca972a72c00ac30cec568c5
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34728
dc.identifier.volume14
dc.pagecount13
dc.publisherScience and Information Organizationen_US
dc.relation.ispartofAll Open Access
dc.relation.ispartofGold Open Access
dc.sourceScopus
dc.sourcetitleInternational Journal of Advanced Computer Science and Applications
dc.subjectcommunication system
dc.subjectintrusion detection system
dc.subjectMachine learning
dc.subjectquality of service
dc.subjectrouting algorithm
dc.subjectClassification (of information)
dc.subjectComplex networks
dc.subjectComputer crime
dc.subjectIntrusion detection
dc.subjectLearning algorithms
dc.subjectMachine learning
dc.subjectMATLAB
dc.subjectNetwork security
dc.subjectRegression analysis
dc.subjectRouting algorithms
dc.subjectCommunications systems
dc.subjectHybrid intrusion detection
dc.subjectIntelligent routing algorithm
dc.subjectIntrusion Detection Systems
dc.subjectMachine-learning
dc.subjectMulti-protocol label-switching network
dc.subjectPerformances evaluation
dc.subjectQuality-of-service
dc.subjectRouting information protocols
dc.subjectService requirements
dc.subjectQuality of service
dc.titleA New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Networken_US
dc.typeArticleen_US
dspace.entity.typePublication
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