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Face Biometrics Under Spoofing Attacks: Vulnerabilities, Countermeasures, Open Issues, and Research Directions

机译:欺骗攻击下的人脸生物识别技术:漏洞,对策,未解决的问题和研究方向

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Among tangible threats and vulnerabilities facing current biometric systems are spoofing attacks. A spoofing attack occurs when a person tries to masquerade as someone else by falsifying data and thereby gaining illegitimate access and advantages. Recently, an increasing attention has been given to this research problem. This can be attested by the growing number of articles and the various competitions that appear in major biometric forums. We have recently participated in a large consortium (TABULARASA) dealing with the vulnerabilities of existing biometric systems to spoofing attacks with the aim of assessing the impact of spoofing attacks, proposing new countermeasures, setting standards/protocols, and recording databases for the analysis of spoofing attacks to a wide range of biometrics including face, voice, gait, fingerprints, retina, iris, vein, electro-physiological signals (EEG and ECG). The goal of this position paper is to share the lessons learned about spoofing and anti-spoofing in face biometrics, and to highlight open issues and future directions.
机译:欺骗攻击是当前生物识别系统面临的明显威胁和漏洞。当一个人试图通过伪造数据伪装成他人,从而获得非法访问和优势时,就会发生欺骗攻击。近来,对该研究问题已经给予了越来越多的关注。主要生物识别论坛上出现的文章数量不断增加和各种竞赛可以证明这一点。我们最近参加了一个大型联盟(TABULARASA),该联盟处理现有生物特征识别系统对欺骗攻击的脆弱性,目的是评估欺骗攻击的影响,提出新的对策,制定标准/协议并记录数据库以进行欺骗分析攻击各种生物特征,包括面部,声音,步态,指纹,视网膜,虹膜,静脉,电生理信号(EEG和ECG)。本立场文件的目的是分享在面部生物识别技术中从欺骗和反欺骗获得的经验教训,并重点介绍未解决的问题和未来的方向。

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