Domenic Forte
Professor | University of Florida
Gainesville, FL, UNITED STATES
Domenic Forte is an expert in the fields of hardware security and assurance, electronic design automation, and microelectronics.
Biography
Domenic Forte is a professor and the Steven A. Yatauro Faculty Fellow at the Department of Electrical and Computer Engineering. He also currently serves as the associate director of the Florida Institute for National Security. His research interests include AI-enabled electronic design automation (EDA), microelectronics supply chain security and assurance (semiconductor IP protection, counterfeit electronics detection and avoidance, hardware Trojan detection and prevention, circuit reverse engineering and anti-reverse engineering), countermeasures against hardware attacks, and hardware security primitives. Domenic is also interested in applications of biometrics, secure multiparty computation, and cyber deception.
Areas of Expertise (5)
Counterfeit Electronics
National Security
Hardware Security
Electronic Design Automation
Artificial Intelligence
Articles (2)
A Fast Object Detection-Based Framework for Via Modeling on PCB X-Ray CT Images
ACM Journal on Emerging Technologies in Computing SystemsDavid Selasi Koblah, et. al
2023-07-03
For successful printed circuit board (PCB) reverse engineering (RE), the resulting device must retain the physical characteristics and functionality of the original. Although the applications of RE are within the discretion of the executing party, establishing a viable, non-destructive framework for analysis is vital for any stakeholder in the PCB industry.
Information Theory-based Evolution of Neural Networks for Side-channel Analysis
IACR Transactions on Cryptographic Hardware and Embedded SystemsRabin Y. Acharya, et. al
2022-11-29
Profiled side-channel analysis (SCA) leverages leakage from cryptographicimplementations to extract the secret key. When combined with advanced methodsin neural networks (NNs), profiled SCA can successfully attack even those crypto-cores assumed to be protected against SCA. Despite the rise in the number ofstudies devoted to NN-based SCA, a range of questions has remained unanswered,namely: how to choose an NN with an adequate configuration, how to tune theNN’s hyperparameters...
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