17 citations · 27 across the 7 of their papers we have counts for
8 papers
Potentials and Pitfalls of Applying Federated Learning in Hardware Assurance
Gijung Lee, Wavid Bowman, Olivia Dizon-Paradis +4
As microelectronics flourish and outsourcing of the design and manufacturing stages of integrated circuits (ICs) and printed circuit boards (PCBs) becomes the norm, microelectronic…
DECIFR: Domain-Aware Exfiltration of Circuit Information from Federated Gradient Reconstruction
Gijung Lee, Wavid Bowman, Olivia P. Dizon-Paradis +4
Federated Learning (FL) is a promising approach for multiparty collaboration as a privacy-preserving technique in hardware assurance, but its security against adversaries with doma…
A Data-Free Membership Inference Attack on Federated Learning in Hardware Assurance
Gijung Lee, Wavid Bowman, Olivia P. Dizon-Paradis +4
Federated Learning (FL) is an emerging solution to the data scarcity problem for training deep learning models in hardware assurance. While FL is designed to enhance privacy by not…
Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunities
Anushka Swarup, Avanti Bhandarkar, Olivia P. Dizon-Paradis +2
Relation extraction is a Natural Language Processing task that aims to extract relationships from textual data. It is a critical step for information extraction. Due to its wide-sc…
In-Situ Thickness Measurement of Die Silicon Using Voltage Imaging for Hardware Assurance
Olivia P. Dizon-Paradis, Nitin Varshney, M Tanjidur Rahman +3
Hardware assurance of electronics is a challenging task and is of great interest to the government and the electronics industry. Physical inspection-based methods such as reverse e…
Framework for Automatic PCB Marking Detection and Recognition for Hardware Assurance
Olivia P. Dizon-Paradis, Daniel E. Capecci, Nathan T. Jessurun +3
A Bill of Materials (BoM) is a list of all components on a printed circuit board (PCB). Since BoMs are useful for hardware assurance, automatic BoM extraction (AutoBoM) is of great…
A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation
David Selasi Koblah, Rabin Yu Acharya, Daniel Capecci +5
Artificial intelligence (AI) and machine learning (ML) techniques have been increasingly used in several fields to improve performance and the level of automation. In recent years,…
FPIC: A Novel Semantic Dataset for Optical PCB Assurance
Nathan Jessurun, Olivia P. Dizon-Paradis, Jacob Harrison +4
Outsourced printed circuit board (PCB) fabrication necessitates increased hardware assurance capabilities. Several assurance techniques based on automated optical inspection (AOI)…