J
Jialiang Peng
Researcher at Heilongjiang University
Publications - 44
Citations - 1165
Jialiang Peng is an academic researcher from Heilongjiang University. The author has contributed to research in topics: Computer science & Biometrics. The author has an hindex of 14, co-authored 33 publications receiving 608 citations. Previous affiliations of Jialiang Peng include Harbin Institute of Technology.
Papers
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Journal ArticleDOI
Deploying Machine and Deep Learning Models for Efficient Data-Augmented Detection of COVID-19 Infections
Ahmed Sedik,Abdullah M. Iliyasu,Abdullah M. Iliyasu,Abdullah M. Iliyasu,Basma Abd El-Rahiem,Mohammed Elsayed Abdel Samea,Asmaa Abdel-Raheem,Mohamed Hammad,Jialiang Peng,Fathi E. Abd El-Samie,Ahmed A. Abd El-Latif,Ahmed A. Abd El-Latif +11 more
TL;DR: The proposed algorithm is effective in performing a rapid and consistent Corona virus diagnosis that is primarily aimed at assisting clinicians in making accurate identification of the virus.
Journal ArticleDOI
A Secure Federated Learning Framework for 5G Networks
TL;DR: A blockchain-based secure FL framework to create smart contracts and prevent malicious or unreliable participants from being involved in FL is proposed, which can effectively deter poisoning and membership inference attacks, thereby improving the security of FL in 5G networks.
Journal ArticleDOI
Multimodal biometric authentication based on score level fusion of finger biometrics
TL;DR: The comparison results suggest that the proposed score level fusion of finger biometrics using triangular norm outperforms the state-of-the-art approaches.
Journal ArticleDOI
Quantum-Inspired Blockchain-Based Cybersecurity: Securing Smart Edge Utilities in IoT-Based Smart Cities
Ahmed A. Abd El-Latif,Bassem Abd-El-Atty,Irfan Mehmood,Khan Muhammad,Salvador E. Venegas-Andraca,Jialiang Peng +5 more
TL;DR: This paper presents a new authentication and encryption protocol based on quantum-inspired quantum walks (QIQW) that can defend against message attack and impersonation attacks, thus ensuring secure transmission of data among IoT devices.
Proceedings ArticleDOI
Finger-vein Verification Using Gabor Filter and SIFT Feature Matching
TL;DR: A novel method to verify the infrared finger-vein patterns is proposed for biometric purposes and the experiment results show that EER is low to 0.46%, which demonstrates the proposed approach is valid and effective for finger-vesin verification.