Hardware trojan detection using machine learning: A tutorial

KI Gubbi, B Saber Latibari, A Srikanth… - ACM Transactions on …, 2023 - dl.acm.org
With the growth and globalization of IC design and development, there is an increase in the
number of Designers and Design houses. As setting up a fabrication facility may easily cost …

Device-specific security challenges and solution in IoT edge computing: a review

A Roy, J Kokila, N Ramasubramanian… - The Journal of …, 2023 - Springer
Rapid growth in IoT technology demands the need for the emergence of new IoT devices.
IoT devices vary in terms of shape, size, storage, battery life, and computational power …

An accurate non-accelerometer-based ppg motion artifact removal technique using cyclegan

AH Afandizadeh Zargari, SAH Aqajari… - ACM Transactions on …, 2023 - dl.acm.org
A photoplethysmography (PPG) is an uncomplicated and inexpensive optical technique
widely used in the healthcare domain to extract valuable health-related information, eg …

Graph neural networks: A powerful and versatile tool for advancing design, reliability, and security of ICs

L Alrahis, J Knechtel, O Sinanoglu - Proceedings of the 28th Asia and …, 2023 - dl.acm.org
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 …

: Backdoor Attack on Graph Neural Networks-Based Hardware Security Systems

L Alrahis, S Patnaik, MA Hanif… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Graph neural networks (GNNs) have shown great success in detecting intellectual property
(IP) piracy and hardware Trojans (HTs). However, the machine learning community has …

Node-wise hardware trojan detection based on graph learning

K Hasegawa, K Yamashita, S Hidano… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In the fourth industrial revolution, securing the protection of supply chains has become an
ever-growing concern. One such cyber threat is a hardware Trojan (HT), a malicious …

[HTML][HTML] A Siamese deep learning framework for efficient hardware Trojan detection using power side-channel data

A Nasr, K Mohamed, A Elshenawy, M Zaki - Scientific Reports, 2024 - nature.com
Abstract Hardware Trojans (HTs) are hidden threats embedded in the circuitry of integrated
circuits (ICs), enabling unauthorized access, data theft, operational disruptions, or even …

Graph neural networks for hardware vulnerability analysis—can you trust your GNN?

L Alrahis, O Sinanoglu - 2023 IEEE 41st VLSI Test Symposium …, 2023 - ieeexplore.ieee.org
The participation of third-party entities in the globalized semiconductor supply chain
introduces potential security vulnerabilities, such as intellectual property piracy and …

Graph based heterogeneous feature extraction for enhanced hardware Trojan detection at gate-level using optimized XGBoost algorithm

MN Devi, V Sankar - Measurement, 2023 - Elsevier
The requirement of reduced production costs in the domain of integrated circuit (IC)
manufacturing and constrained time-to-market are met at the cost of a plethora of security …

Automated Hardware Trojan Detection at LUT Using Explainable Graph Neural Networks

L Wu, H Su, X Zhang, Y Tai, H Li… - 2023 IEEE/ACM …, 2023 - ieeexplore.ieee.org
Trojan horses represent a major threat to hardware security and trust. In this work, we
propose a novel hardware Trojan detection method based on explainable graph neural …