用于安全生物识别系统组件评估的机器学习方法

Bilgehan Arslan, Mehtap Ülker, Ş. Sağiroğlu
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引用次数: 3

摘要

本文提供了生物识别系统的理论,方法,技术,标准和框架的全面概述。为了确保生物识别系统中使用的设备的安全性,确保特征提取的安全性,在生物识别数据库中提供安全的数据存储,维护生物识别应用中使用的传输通道免受漏洞的影响,并确保从智能决策机制中获得的结果的正确性,对2007-2017年期间进行的研究进行了审查。分析了用于检测和保护现有攻击的机器学习技术,分享了获得的结果,并在研究的最后一部分提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Methods Used in Evaluations of Secure Biometric System Components
This paper provides a comprehensive overview of theories, methodologies, techniques, standards and frameworks of biometric systems. The studies conducted between 2007-2017 are examined in order to ensure the security of the equipment used in a biometric system, to secure the characteristic feature extraction, to provide secure data storage in the biometric database, to maintain transmission channels used in biometric applications from vulnerabilities, and to ensure the correctness of the results obtained from intelligent decision mechanism. Machine learning techniques used to detect and protect existing attacks are analyzed, obtained results are shared and recommendations are made in the last part of the study.
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