7 citations · 10 across the 2 of their papers we have counts for
12 papers
MaliGNNoma: GNN-Based Malicious Circuit Classifier for Secure Cloud FPGAs
Lilas Alrahis, Hassan Nassar, Jonas Krautter +4
The security of cloud field-programmable gate arrays (FPGAs) faces challenges from untrusted users attempting fault and side-channel attacks through malicious circuit configuration…
AutoLock: Automatic Design of Logic Locking with Evolutionary Computation
Zeng Wang, Lilas Alrahis, Dominik Sisejkovic +1
Logic locking protects the integrity of hardware designs throughout the integrated circuit supply chain. However, recent machine learning (ML)-based attacks have challenged its fun…
FPGA-Patch: Mitigating Remote Side-Channel Attacks on FPGAs using Dynamic Patch Generation
Mahya Morid Ahmadi, Lilas Alrahis, Ozgur Sinanoglu +1
We propose FPGA-Patch, the first-of-its-kind defense that leverages automated program repair concepts to thwart power side-channel attacks on cloud FPGAs. FPGA-Patch generates isof…
Graph Neural Networks for Hardware Vulnerability Analysis -- Can you Trust your GNN?
Lilas Alrahis, Ozgur Sinanoglu
The participation of third-party entities in the globalized semiconductor supply chain introduces potential security vulnerabilities, such as intellectual property piracy and hardw…
PoisonedGNN: Backdoor Attack on Graph Neural Networks-based Hardware Security Systems
Lilas Alrahis, Satwik Patnaik, Muhammad Abdullah Hanif +2
Graph neural networks (GNNs) have shown great success in detecting intellectual property (IP) piracy and hardware Trojans (HTs). However, the machine learning community has demonst…
DNN-Alias: Deep Neural Network Protection Against Side-Channel Attacks via Layer Balancing
Mahya Morid Ahmadi, Lilas Alrahis, Ozgur Sinanoglu +1
Extracting the architecture of layers of a given deep neural network (DNN) through hardware-based side channels allows adversaries to steal its intellectual property and even launc…