Yanushkevich, Svetlana, Howells, Gareth, Crockett, Keely, O'Shea, Jim, Oliveira, H.C.R, Guest, Richard, Shmerko, Vlad (2020) Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources. In: Proceedings of the First IEEE International Conference on Cognitive Machine Intelligence. Proceedings of the First IEEE International Conference on Cognitive Machine Intelligence. . IEEE ISBN 978-1-72816-738-1. E-ISBN 978-1-72816-737-4. (doi:10.1109/CogMI48466.2019.00014) (KAR id:79327)
PDF
Author's Accepted Manuscript
Language: English |
|
Download this file (PDF/703kB) |
|
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: http://dx.doi.org/10.1109/CogMI48466.2019.00014 |
Abstract
This work advocates for cognitive biometric-enabled systems that integrate identity management, risk assessment and trust assessment. The cognitive identity management process is viewed as a multi-state dynamical system, and probabilistic reasoning is used for modeling of this process. This paper describes an approach to design a platform for risk and trust modeling and evaluation in the cognitive identity management built upon processing heterogeneous data including biometrics, other sensory data and digital ID. The core of an approach is the perception-action cycle of each system state. Inference engine is a causal network that uses various uncertainty metrics and reasoning mechanisms including Dempster-Shafer and Dezert- Smarandache beliefs.
Item Type: | Conference or workshop item (Paper) |
---|---|
DOI/Identification number: | 10.1109/CogMI48466.2019.00014 |
Uncontrolled keywords: | biometrics, trust, cybersecurity |
Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Gareth Howells |
Date Deposited: | 17 Dec 2019 11:30 UTC |
Last Modified: | 09 Dec 2022 02:38 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/79327 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):