Deep Learning Modalities for Biometric Alteration Detection in 5G Networks-Based Secure Smart Cities

Deep Learning Modalities for Biometric Alteration Detection in 5G Networks-Based Secure Smart Cities

Smart cities and their applications have become attractive research fields birthing numerous technologies. Fifth generation (5G) networks are important components of smart cities, where intelligent access control is deployed for identity authentication, online banking, and cyber security. To assure...

Full description

Bibliographic Details
Main Authors: Ahmed Sedik, Lo'Ai Tawalbeh, Mohamed Hammad, Ahmed A. Abd El-Latif, Ghada M. El-Banby, Ashraf A. M. Khalaf, Fathi E. Abd El-Samie, Abdullah M. Iliyasu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep learning
cyber threats
biometric alteration detection
cybersecurity
5G network
smart city
Online Access:https://ieeexplore.ieee.org/document/9450808/

Internet

https://ieeexplore.ieee.org/document/9450808/

Similar Items