Multimodal Cognitive Authentication for Zero-Trust Security: Next-Generation User Verification with Advanced Biometric Integration

Authors

Subhasis Kundu

Abstract

This paper presents a cutting-edge multimodal cognitive authentication system designed to bolster security within a zero-trust framework. This innovative approach integrates voice recognition, gait analysis, and behavioral biometrics to create a comprehensive, multi-layered authentication process that counters the threats posed by deepfake and spoofing attacks [1] . This study assessed the system's effectiveness in real-world scenarios by examining its accuracy, false acceptance rates, and user experience. The results demonstrate a notable enhancement in security compared with single-factor authentication methods, with a 98.7% decrease in successful spoofing attempts. The adaptive learning features of the system allow for the ongoing refinement of user profiles, enhancing its ability to withstand emerging threats. By incorporating multiple biometric modalities, the proposed authentication solution addresses the shortcomings of conventional biometric methods and strengthens the security of the zero-trust architectures. This study underscores the potential of multimodal cognitive authentication in delivering a more secure and user-friendly access control mechanism for high-security settings. Future research avenues include investigating emerging biometric modalities, harnessing advancements in artificial intelligence and machine learning, and combining the system with other security technologies to develop a comprehensive and robust security framework.

Keywords

Multimodal Authentication, Zero-Trust Security, Biometric Integration, Cognitive Biometrics, Deepfake Detection, Spoofing Attacks, Gait Analysis, Voice Recognition, Behavioral Biometrics, Adaptive Learning

Multimodal Cognitive Authentication for Zero-Trust Security: Next-Generation User Verification with Advanced Biometric Integration. Subhasis Kundu. 2020. IJIRCT, Volume 6, Issue 2. Pages 1-9. https://www.ijirct.org/viewPaper.php?paperId=2503084