{"title":"Cancellable multi-modal biometrie authentication for cloud based mobilityfirst like environment","authors":"M. Alam, Haozhang Li, M. Chowdhury","doi":"10.1109/ICIEA.2016.7603637","DOIUrl":null,"url":null,"abstract":"In this research, we propose a secure multi-modal biometric authentication that will have cancellable property. Cloud servers need to have the confidential information mobile and ready in case of cancellation so that the same user can authenticate or identify using the same authentication process when joining to other clouds. However, a cloud server needs to be careful transferring biometric data to other cloud during busy time, since biometric data is sensitive to bit error rate that may adversely affect the false acceptance or rejection rate. As such another key contribution of this paper is to provide a decision making model for biometric/confidential data transfer among clouds in busy time in order to avoid network congestion. The work presented in this research is also a good fit during migration of today's internet into MobilityFirst architecture while biometric information in a locality is being shared by cloud servers and service is being provided at the same time.","PeriodicalId":283114,"journal":{"name":"2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2016.7603637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this research, we propose a secure multi-modal biometric authentication that will have cancellable property. Cloud servers need to have the confidential information mobile and ready in case of cancellation so that the same user can authenticate or identify using the same authentication process when joining to other clouds. However, a cloud server needs to be careful transferring biometric data to other cloud during busy time, since biometric data is sensitive to bit error rate that may adversely affect the false acceptance or rejection rate. As such another key contribution of this paper is to provide a decision making model for biometric/confidential data transfer among clouds in busy time in order to avoid network congestion. The work presented in this research is also a good fit during migration of today's internet into MobilityFirst architecture while biometric information in a locality is being shared by cloud servers and service is being provided at the same time.