학술논문

Risk Inference Models for Security Applications
Document Type
Conference
Source
2019 Eighth International Conference on Emerging Security Technologies (EST) Emerging Security Technologies (EST), 2019 Eighth International Conference on. :1-6 Jul, 2019
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Uncertainty
Measurement
Engines
Bayes methods
Reliability
Biological system modeling
Probabilistic logic
graph-based models
machine reasoning
probabilistic inference
biometrics
uncertainty metric
causal network
Language
ISSN
2472-7601
Abstract
This paper focuses on the causal graph models for machine reasoning and its applications to risk assessment in biometrics. Specifically, we consider probabilistic inference performed on video data, images, speech and other human biometric data. In our approach, called the Multi-metric Inference Engine, the Bayesian network are constructed using different metrics of uncertainty, such as point probability, interval probability, fuzzy probability, and Dempster-Shafer model. We demonstrate the Inference Engine techniques using biometric-enabled security scenarios and propose a software tool for experimental study.