{"title":"Cybersecurity Risk Management in Identity Systems using Biometric-based Multimodal Authentication.","authors":"A. Talabi, O. Longe, A. A. Muhammad, K. Olusanya","doi":"10.22624/aims/isteams-2021/v28n2p5","DOIUrl":null,"url":null,"abstract":"This increasing inter-connectivity of systems and dependence on computer and internet-based networks has made Cybersecurity related risks management issues major considerations in designing, developing and managing identity systems. Thus, this paper investigates Cybersecurity and related risk management challenges in Identity Management Systems by undertaking a comparative analysis of different biometric traits. The analysis proved that biometric-based multimodal systems are more secure than uni-modal systems with high accuracy rates. Also, it produced minimal false acceptance and false rejection rates. The biometric-based multi-modal authentication systems will assist organizations to restrict access to authorized users and protect digital assets by ensuring confidentiality, integrity and availability. Keywords: Cybersecurity, Risk, Identity, Biometrics, Multimodal, Behavioural, Fusion","PeriodicalId":332710,"journal":{"name":"Proceedings of the 28th iSTEAMS Multidisciplinary & Inter-tertiary Research Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 28th iSTEAMS Multidisciplinary & Inter-tertiary Research Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22624/aims/isteams-2021/v28n2p5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This increasing inter-connectivity of systems and dependence on computer and internet-based networks has made Cybersecurity related risks management issues major considerations in designing, developing and managing identity systems. Thus, this paper investigates Cybersecurity and related risk management challenges in Identity Management Systems by undertaking a comparative analysis of different biometric traits. The analysis proved that biometric-based multimodal systems are more secure than uni-modal systems with high accuracy rates. Also, it produced minimal false acceptance and false rejection rates. The biometric-based multi-modal authentication systems will assist organizations to restrict access to authorized users and protect digital assets by ensuring confidentiality, integrity and availability. Keywords: Cybersecurity, Risk, Identity, Biometrics, Multimodal, Behavioural, Fusion