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Advanced threats are increasingly challenging biometric identification systems, undermining their security and reliability. The present in-depth analysis examines vulnerabilities in fingerprint, facial recognition, iris scan, and voice identification systems through a systematic review of 137 peer-reviewed articles published between 2018 and 2024. Our study reveals four critical new threats: presentation attacks with synthetic biometrics (40% increase since 2020), adversarial machine learning attacks on underlying algorithms (more than 85% success rate against unsecured systems), zero-day vulnerabilities in embedded hardware (affecting 62% of commercial solutions), and privacy concerns due to biometric template theft. Effective mitigation entails multimodal fusion methods minimizing exposure by 76%, liveness detection protocols founded on randomized challenge-response methods, privacy-preserving biometric cryptosystems, and system-level security policies that include risk-based authentication systems. We discover that although biometric authentication offers considerable security advantages, deployment must entail layered defenses addressing technical as well as procedural exposures to maintain integrity against advanced threat vectors.

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Emerging Threats and Mitigation Strategies in Biometric Authentication Systems

  • 会议论文

  • 发表日期：

    2026年

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  • Ashish Kargeti,
  • Taruna Chopra

摘要

Advanced threats are increasingly challenging biometric identification systems, undermining their security and reliability. The present in-depth analysis examines vulnerabilities in fingerprint, facial recognition, iris scan, and voice identification systems through a systematic review of 137 peer-reviewed articles published between 2018 and 2024. Our study reveals four critical new threats: presentation attacks with synthetic biometrics (40% increase since 2020), adversarial machine learning attacks on underlying algorithms (more than 85% success rate against unsecured systems), zero-day vulnerabilities in embedded hardware (affecting 62% of commercial solutions), and privacy concerns due to biometric template theft. Effective mitigation entails multimodal fusion methods minimizing exposure by 76%, liveness detection protocols founded on randomized challenge-response methods, privacy-preserving biometric cryptosystems, and system-level security policies that include risk-based authentication systems. We discover that although biometric authentication offers considerable security advantages, deployment must entail layered defenses addressing technical as well as procedural exposures to maintain integrity against advanced threat vectors.