Securing Deep Learning Based Edge Finger Vein Biometrics With Binary Decision Diagram

• Published in: IEEE transactions on industrial informatics Vol. 15; no. 7; pp. 4244 - 4253
• Main Authors: Yang, Wencheng, Wang, Song, Hu, Jiankun, Zheng, Guanglou, Yang, Jucheng, Valli, Craig
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial intelligence; Artificial intelligence (AI); Artificial neural networks; binary decision diagram (BDD); biometric template protection; Biometrics; Biometrics (access control); Deep learning; edge biometrics; edge computing; Feature extraction; finger vein; Machine learning; machine/deep learning; Multilayers; Neural networks; Recognition; Security

With built-in artificial intelligence (AI), edge devices, e.g., smart cameras, can perform tasks like detecting and tracking individuals, which is referred to as edge biometrics. As a driving force for AI, machine/deep learning plays a critical role in edge biometrics. Machine/deep learning based ed...