{"title":"A Hybrid Intrusion Detection System for IoT Applications with Constrained Resources","authors":"Chao Wu, Yuan’an Liu, Fan Wu, Feng Liu, Hui Lu, Wenhao Fan, B. Tang","doi":"10.4018/ijdcf.2020010106","DOIUrl":null,"url":null,"abstract":"NetworksecurityandnetworkforensicstechnologiesfortheInternetofThings(IoT)needspecial considerationduetoresource-constraints.CybercrimesconductedinIoTfocusonnetworkinformation andenergy sources.Graph theory is adopted to analyze the IoTnetworkandahybrid Intrusion DetectionSystem(IDS)isproposed.ThehybridIDSconsistsofCentralizedandActiveMalicious NodeDetection(CAMD)andDistributedandPassiveEEA(EnergyExhaustionAttack)Resistance (DPER).CAMDisintegratedinthegeneticalgorithm-baseddatagatheringscheme.CAMDdetects maliciousnodesmanipulatedbycybercriminalsandprovidesdigitalevidenceforforensics.DPERis implementedinasetofcommunicationprotocolstoalleviatetheimpactofEEAattacks.Simulation experiments conducted on NS-3 platform showed the hybrid IDS proposed detected and traced maliciousnodespreciselywithoutcompromisingenergyefficiency.Besides, the impactofEEA attacksconductedbycybercriminalswaseffectivelyalleviated. KeywoRDS Cybercrime, Energy Efficiency, Genetic Algorithm, Graph Theory, Internet Of Things, Network Forensics","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"58 1","pages":"109-130"},"PeriodicalIF":0.6000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Digital Crime and Forensics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijdcf.2020010106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 6
资源受限的物联网应用混合入侵检测系统
NetworksecurityandnetworkforensicstechnologiesfortheInternetofThings(IoT)needspecial considerationduetoresource-constraints。CybercrimesconductedinIoTfocusonnetworkinformation andenergy来源。Graph采用理论来分析IoTnetworkandahybrid intrusion_ DetectionSystem(IDS)isproposed。ThehybridIDSconsistsofCentralizedandActiveMalicious NodeDetection(CAMD)andDistributedandPassiveEEA(EnergyExhaustionAttack)Resistance (DPER).CAMDisintegratedinthegeneticalgorithm-baseddatagatheringscheme。CAMDdetects maliciousnodesmanipulatedbycybercriminalsandprovidesdigitalevidenceforforensics。DPERis implementedinasetofcommunicationprotocolstoalleviatetheimpactofEEAattacks。Simulation在ns -3平台上进行的实验显示了所提出的混合ids,并进行了检测和跟踪maliciousnodespreciselywithoutcompromisingenergyefficiency。Besides, the impactofEEA attacksconductedbycybercriminalswaseffectivelyalleviated。关键词:网络犯罪,能效,遗传算法,图论,物联网,网络取证
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