access icon free Biometric ontology for semantic biometric-as-a-service (BaaS) applications: a border security use case

With the fast adoption of cloud computing, the use of biometric technologies has evolved to a different way of providing security, preserving privacy, and analysing personal traits for various purposes. The main components of any biometric system, such as biometric sensing, data gathering, feature extraction, identification, verification, recognition, and analytics, are now handled over distributed networks. Many of the biometric system services are presented over such networks which are followed by the creation of a new concept ‘biometric-as-a-service (BaaS)’. Recent BaaS approaches usually focus on identifying the effective distributed architectures, policies, and use case recommendations. However, there is a strong need to focus on developing a semantic framework which should rely on a biometric ontology. This study presents such an ontology covering the uses of different biometric modalities, evaluation and assessment of biometric systems, modelling biometric processes, and analyses through interlinked relations with biometric stakeholders. In order to shed light on how such an ontology is useful for BaaS solutions, a case study focusing on the various uses of biometric modalities is presented. The selected use case addresses the asylum seeker or immigrant identification problems regarding the border security challenges where facial biometrics are benefited.

Inspec keywords: national security; cloud computing; face recognition; ontologies (artificial intelligence); biometrics (access control); feature extraction; data privacy

Other keywords: BaaS solutions; biometric system services; biometric sensing; effective distributed architectures; border security challenges; case study; distributed networks; biometric ontology; selected use case; recent BaaS approaches; facial biometrics; biometric technologies; different biometric modalities; biometric stakeholders; use case recommendations; modelling biometric processes; analysing personal traits; fast adoption; biometric-as-a-service applications

Subjects: Computer vision and image processing techniques; Data security

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-bmt.2018.5067
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content/journals/10.1049/iet-bmt.2018.5067
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