Recent Advances in Biometric Security in IoT Based on Machine Learning

Dear Colleagues,

Internet of Things (IoT) applications has been deployed in a wide variety of critical infrastructure and applications ranging from transportation, healthcare, and supply chain. While IoT brings a number of benefits including convenience and efficiency, it also introduces a number of emerging threats. With the emergence of the Internet-of-Things (IoT), there is a growing need for access control and data protection. Biometric-based authentication is promising for IoT due to its convenient nature and lower susceptibility to attacks. Additionally, machine learning and deep learning techniques are delivering a promising solution to biometric systems and to increase the accuracy and plays a decisive role for presentation attack detection.

The goal of this special issue is to solicit high quality contributions on: (i) investigating the usage of deep learning and biometric systems in the context of IoT applications; (ii) novel techniques in biometric deep fakes and digital data forensics, particularly by exploiting, but not limited to, deep learning approaches.

Prof. Dr. Nima Karimian
Prof. Dr. Tempestt Neal
Guest Editors

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