Risk Assessment in Authentication Machines

Eastwood, Shawn; Yanushkevich, Svetlana

doi:10.1007/978-3-319-26450-9_15

Cited by 8 publications

(13 citation statements)

References 33 publications

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“…The procedure will be the same except for the CUTs. The approach here uses theory from [17], [20]. However, an alternative approach has been developed [50].…”

Section: Ds Belief Measuresmentioning

confidence: 99%

Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources

Yanushkevich

Howells

Crockett

et al. 2019

2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI)

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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.

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“…The procedure will be the same except for the CUTs. The approach here uses theory from [17], [20]. However, an alternative approach has been developed [50].…”

Section: Ds Belief Measuresmentioning

confidence: 99%

Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources

Yanushkevich

Howells

Crockett

et al. 2019

2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI)

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“…Bayesian networks are commonly used for modeling the vulnerability of airport infrastructure, attacks, and traveler risk assessment. 2,3,27…”

Section: Survey On Uncertainty Representation and Processing In Mandsmentioning

confidence: 99%

“…The DS measures can be useful for some specific scenarios of authentication and risk assessment for border crossing applications. 2 There is a DS extension known as Dezert–Smarandache (DSm) theory 32 that has been used for the design of large-scale military recommendation systems. 33…”

Section: Survey On Uncertainty Representation and Processing In Mandsmentioning

confidence: 99%

“…41 In addition, a formal notion of a Bayesian network with incorporated DS measures and its implementation have been introduced in the authors’ previous papers. 2…”

Section: Survey On Uncertainty Representation and Processing In Mandsmentioning

confidence: 99%

“…Next, we will construct a belief network describing the above scenario using (a) a traditional Bayesian network, and (b) a “Dempster–Shafer Bayesian Network” (DS-BN). 2 Figure 4(a) depicts a traditional Bayesian network that describes a simple causal relationship between W , I , and M , where I is influenced by W , and M is influenced by I . Figure 4(b) depicts a DS-BN that has the same causal relationships as the Bayesian network in Figure 4(a), but with some uncertainty introduced into the probability values.…”

Section: Simplest Watchlist Check Scenariomentioning

confidence: 99%

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Understanding and taxonomy of uncertainty in modeling, simulation, and risk profiling for border control automation

Yanushkevich

Eastwood

Drahanský

et al. 2016

Journal of Defense Modeling & Simulation

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This paper addresses the problem of trust in Modeling and Simulation (M&S) technologies, and uncertainty in applications to homeland security. The key goal of this paper is an extension of the notion of trusted M&S techniques for traveler risk assessment in mass-transit applications such as e-borders. Theories of uncertainty suggest that different understandings of uncertainty result in different mechanisms of its reduction. We show that a taxonomy of uncertainty that is accepted in philosophical studies, as well as the NATO methodology of uncertainty assessment (known as the Admiralty Code), can be useful in M&S. This paper overviews various approaches to M&S and focuses on a framework that is based on multi-source fusion mechanisms using Dempster–Shafer (DS) theory. The DS metric is useful for the development of simulators, recommender machines, and risk profilers when expert knowledge is given in an imprecise form. The difference between the Bayesian and DS metrics is introduced via a demonstrative experiment from the area of traveler risk assessment using a biometric-enabled watchlist.

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