44 citations · 70 across the 22 of their papers we have counts for
6 papers · 1 filter
Graph Neural Networks: A Powerful and Versatile Tool for Advancing Design, Reliability, and Security of ICs
Lilas Alrahis, Johann Knechtel, Ozgur Sinanoglu
Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in learning and predicting on large-scale data present in social networks, biology, etc. Since…
Security Closure of IC Layouts Against Hardware Trojans
Fangzhou Wang, Qijing Wang, Bangqi Fu +7
Due to cost benefits, supply chains of integrated circuits (ICs) are largely outsourced nowadays. However, passing ICs through various third-party providers gives rise to many thre…
AppGNN: Approximation-Aware Functional Reverse Engineering using Graph Neural Networks
Tim Bucher, Lilas Alrahis, Guilherme Paim +3
The globalization of the Integrated Circuit (IC) market is attracting an ever-growing number of partners, while remarkably lengthening the supply chain. Thereby, security concerns,…
Embracing Graph Neural Networks for Hardware Security (Invited Paper)
Lilas Alrahis, Satwik Patnaik, Muhammad Shafique +1
Graph neural networks (GNNs) have attracted increasing attention due to their superior performance in deep learning on graph-structured data. GNNs have succeeded across various dom…
GNN4REL: Graph Neural Networks for Predicting Circuit Reliability Degradation
Lilas Alrahis, Johann Knechtel, Florian Klemme +2
Process variations and device aging impose profound challenges for circuit designers. Without a precise understanding of the impact of variations on the delay of circuit paths, gua…
NeuroUnlock: Unlocking the Architecture of Obfuscated Deep Neural Networks
Mahya Morid Ahmadi, Lilas Alrahis, Alessio Colucci +2
The advancements of deep neural networks (DNNs) have led to their deployment in diverse settings, including safety and security-critical applications. As a result, the characterist…