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Published in:
Recent Advances in Computational Intelligence in Defense and Security Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Risk Assessment in Authentication Machines

Authors : S. Eastwood, S. Yanushkevich

Published in: Recent Advances in Computational Intelligence in Defense and Security

Publisher: Springer International Publishing

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Abstract

This work introduces an approach to building a risk profiler for use in authentication machines. Authentication machine application scenarios include the security of large public events, pandemic prevention, and border crossing automation. The proposed risk profiler provides a risk assessment at all phases of the authentication machine life-cycle. The key idea of our approach is to utilize the advantages of belief networks to solve large-scale multi-source fusion problems. We extend the abilities of belief networks by incorporating Dempster-Shafer Theory measures, and report the design techniques by using the results of the prototyping of possible attack scenarios. The software package is available for researchers.

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previous chapter A Dual-Purpose Memory Approach for Dynamic Particle Swarm Optimization of Recurrent Problems
next chapter Game Theoretical Approach for Dynamic Active Patrolling in a Counter-Piracy Framework
Footnotes
1
The e-passport and e-ID are defined by the ICAO standard, and are the key components of advanced border control technologies [54]. The face was recommended as the primary biometric, mandatory for global interoperability in the passport inspection systems. Fingerprint and iris were recommended as secondary biometrics.
 
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Metadata
Title
Risk Assessment in Authentication Machines
Authors
S. Eastwood
S. Yanushkevich
Copyright Year
2016
Book
Recent Advances in Computational Intelligence in Defense and Security

Print ISBN: 978-3-319-26448-6

Electronic ISBN: 978-3-319-26450-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26450-9_15

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