A New Generation Wireless Biometric System with Deep Feature Fusion in IoT


연구 분야: Infrastructure



학회: International Conference on Ubiquitous Security


초록

While traditional biometric systems are well-established in the industry, they come with several drawbacks, such as being intrusive to privacy, requiring user attention, and lacking ubiquity. This paper introduces a new biometric system using a cyber-physical approach with Wi-Fi-integrated devices. This first develops a security zone using Wi-Fi-integrated devices and then scans a person entering the security zones using wireless signals. Acquired wireless signals are utilized to extract biometric multi-signature features. The proposed system employs a bio-electromagnetic human model and deep learning algorithms, including a two-layer CNN architecture, to identify the person. Preliminary results show that the proposed Wi-ID achieves up to 88% accuracy in detecting a person through biometric signatures.


Author Profile
Zakirul Alam Bhuiyan

Department of Computer and Information Sciences Fordham University Bronx NY 10458 USA

Andorra
Author Profile
Muhammad Ehsan

Department of Computer and Information Sciences Fordham University Bronx NY 10458 USA

Andorra
Author Profile
Yuanfang Chen

School of Cyberspace Hangzhou Dianzi University and The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou 310018 China

Andorra

📄 논문 정보

발행 연도 2025년
인용수 0
출판 국가 Andorra
사이트 Springer
좋아요 수 0

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