52 citations · 584 across the 43 of their papers we have counts for
38 papers · 1 filter
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…
ALMOST: Adversarial Learning to Mitigate Oracle-less ML Attacks via Synthesis Tuning
Animesh Basak Chowdhury, Lilas Alrahis, Luca Collini +5
Oracle-less machine learning (ML) attacks have broken various logic locking schemes. Regular synthesis, which is tailored for area-power-delay optimization, yields netlists where k…
TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection
Hazem Lashen, Lilas Alrahis, Johann Knechtel +1
We propose TrojanSAINT, a graph neural network (GNN)-based hardware Trojan (HT) detection scheme working at the gate level. Unlike prior GNN-based art, TrojanSAINT enables both pre…
X-Volt: Joint Tuning of Driver Strengths and Supply Voltages Against Power Side-Channel Attacks
Saideep Sreekumar, Mohammed Ashraf, Mohammed Nabeel +2
Power side-channel (PSC) attacks are well-known threats to sensitive hardware like advanced encryption standard (AES) crypto cores. Given the significant impact of supply voltages…
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…
Hardware Trojan Threats to Cache Coherence in Modern 2.5D Chiplet Systems
Gino A. Chacon, Charles Williams, Johann Knechtel +2
As industry moves toward chiplet-based designs, the insertion of hardware Trojans poses a significant threat to the security of these systems. These systems rely heavily on cache c…
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…
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…
MuxLink: Circumventing Learning-Resilient MUX-Locking Using Graph Neural Network-based Link Prediction
Lilas Alrahis, Satwik Patnaik, Muhammad Shafique +1
Logic locking has received considerable interest as a prominent technique for protecting the design intellectual property from untrusted entities, especially the foundry. Recently,…
UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction
Lilas Alrahis, Satwik Patnaik, Muhammad Abdullah Hanif +2
Logic locking aims to prevent intellectual property (IP) piracy and unauthorized overproduction of integrated circuits (ICs). However, initial logic locking techniques were vulnera…
GNNUnlock: Graph Neural Networks-based Oracle-less Unlocking Scheme for Provably Secure Logic Locking
Lilas Alrahis, Satwik Patnaik, Faiq Khalid +4
In this paper, we propose GNNUnlock, the first-of-its-kind oracle-less machine learning-based attack on provably secure logic locking that can identify any desired protection logic…
UNSAIL: Thwarting Oracle-Less Machine Learning Attacks on Logic Locking
Lilas Alrahis, Satwik Patnaik, Johann Knechtel +4
Logic locking aims to protect the intellectual property (IP) of integrated circuit (IC) designs throughout the globalized supply chain. The SAIL attack, based on tailored machine l…
2.5D Root of Trust: Secure System-Level Integration of Untrusted Chiplets
Mohammed Nabeel, Mohammed Ashraf, Satwik Patnaik +3
Dedicated, after acceptance and publication, in memory of the late Vassos Soteriou. For the first time, we leverage the 2.5D interposer technology to establish system-level securit…
Attacking Split Manufacturing from a Deep Learning Perspective
Haocheng Li, Satwik Patnaik, Abhrajit Sengupta +5
The notion of integrated circuit split manufacturing which delegates the front-end-of-line (FEOL) and back-end-of-line (BEOL) parts to different foundries, is to prevent overproduc…
Power Side-Channel Attacks in Negative Capacitance Transistor (NCFET)
Johann Knechtel, Satwik Patnaik, Mohammed Nabeel +5
Side-channel attacks have empowered bypassing of cryptographic components in circuits. Power side-channel (PSC) attacks have received particular traction, owing to their non-invasi…
Benchmarking at the Frontier of Hardware Security: Lessons from Logic Locking
Benjamin Tan, Ramesh Karri, Nimisha Limaye +33
Integrated circuits (ICs) are the foundation of all computing systems. They comprise high-value hardware intellectual property (IP) that are at risk of piracy, reverse-engineering,…
Obfuscating the Interconnects: Low-Cost and Resilient Full-Chip Layout Camouflaging
Satwik Patnaik, Mohammed Ashraf, Ozgur Sinanoglu +1
Layout camouflaging can protect the intellectual property of modern circuits. Most prior art, however, incurs excessive layout overheads and necessitates customization of active-de…
DynUnlock: Unlocking Scan Chains Obfuscated using Dynamic Keys
Nimisha Limaye, Ozgur Sinanoglu
Outsourcing in semiconductor industry opened up venues for faster and cost-effective chip manufacturing. However, this also introduced untrusted entities with malicious intent, to…
ScanSAT: Unlocking Static and Dynamic Scan Obfuscation
Lilas Alrahis, Muhammad Yasin, Nimisha Limaye +4
While financially advantageous, outsourcing key steps, such as testing, to potentially untrusted Outsourced Assembly and Test (OSAT) companies may pose a risk of compromising on-ch…