Abstract

The rapid growth of IoT and edge devices has created new demands for lightweight and hardware-rooted security mechanisms. Physical Unclonable Functions (PUFs) have emerged as a promising primitive due to their efficiency and resistance to physical attacks. Nevertheless, recent advances in machine learning have revealed significant vulnerabilities in PUF-based designs, raising concerns about their long-term security. This talk introduces the foundations and applications of PUFs in key generation and authentication, examines the evolving threat landscape with a focus on modeling attacks, and reviews representative countermeasures. The presentation also highlights recent research on adversarial-based defenses and provably secure PUF constructions, demonstrating how reliability and noise can be transformed into security advantages. 

Bio.

  Dr. Chia-Chih Lin received his Ph.D. degree in Computer Science and Information Engineering from National Taiwan University (NTU) in 2023. He is currently an Assistant Professor in the Department of Computer Science and Information Engineering at National Taiwan University of Science and Technology (NTUST). His research interests focus on Physical Unclonable Functions (PUFs), with an emphasis on algorithmic approaches to analyzing and improving their security and performance. His broader research areas also include secure artificial intelligence, privacy-preserving technologies, and confidential computing. 

All faculty and students are welcome to join.