Physical Sciences and Mathematics Commons^™

Deep Learning Modalities For Biometric Alteration Detection In 5g Networks-Based Secure Smart Cities, Ahmed Sedik, Lo'ai A. Tawalbeh, Mohamed Hammad, Ahmed A. Abd El-Latif, Ghada M. El-Banby, Ashref A.M. Khalaf, Fathi E. Abd El-Samie, Abdullah M. Iliyasu

Computer Science Faculty Publications

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 secure transactions and to protect user’s identities against cybersecurity threats, strong authentication techniques should be used. The prevalence of biometrics, such as fingerprints, in authentication and identification makes the need to safeguard them important across different areas of smart applications. Our study presents a system to detect alterations to biometric modalities to discriminate pristine, adulterated, and fake biometrics in 5G-based smart …