Related papers: TROJAN-GUARD: Hardware Trojans Detection Using GNN…
Many fabless semiconductor companies outsource their designs to third-party fabrication houses. As trustworthiness of chain after outsourcing including fabrication houses is not established, any adversary in between, with malicious intent…
When the training data are maliciously tampered, the predictions of the acquired deep neural network (DNN) can be manipulated by an adversary known as the Trojan attack (or poisoning backdoor attack). The lack of robustness of DNNs against…
Hardware trojans are malicious circuits which compromise the functionality and security of an integrated circuit (IC). These circuits are manufactured directly into the silicon and cannot be fixed by security patches like software. The…
Recently, Deep Learning (DL), especially Convolutional Neural Network (CNN), develops rapidly and is applied to many tasks, such as image classification, face recognition, image segmentation, and human detection. Due to its superior…
Electronic Design Automation (EDA) industry heavily reuses third party IP cores. These IP cores are vulnerable to insertion of Hardware Trojans (HTs) at design time by third party IP core providers or by malicious insiders in the design…
The availability of wide-ranging third-party intellectual property (3PIP) cores enables integrated circuit (IC) designers to focus on designing high-level features in ASICs/SoCs. The massive proliferation of ICs brings with it an increased…
The globalized semiconductor supply chain has made Hardware Trojans (HT) a significant security threat to embedded systems, necessitating the design of efficient and adaptable detection mechanisms. Despite promising machine learning-based…
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-/post-silicon HT detection. TrojanSAINT leverages a…
With the rising popularity of machine learning and the ever increasing demand for computational power, there is a growing need for hardware optimized implementations of neural networks and other machine learning models. As the technology…
Software-exploitable Hardware Trojans (HTs) enable attackers to execute unauthorized software or gain illicit access to privileged operations. This manuscript introduces a hardware-based methodology for detecting runtime HT activations…
Neuromorphic computing based on spiking neural networks (SNNs) is emerging as a promising alternative to traditional artificial neural networks (ANNs), offering unique advantages in terms of low power consumption. However, the security…
Hardware Trojans (HTs) have drawn more and more attention in both academia and industry because of its significant potential threat. In this paper, we proposed a novel HT detection method using information entropy based clustering, named…
Deep Neural Networks (DNNs) have found extensive applications in safety-critical artificial intelligence systems, such as autonomous driving and facial recognition systems. However, recent research has revealed their susceptibility to…
High-level synthesis (HLS) tools have provided significant productivity enhancements to the design flow of digital systems in recent years, resulting in highly-optimized circuits, in terms of area and latency. Given the evolution of…
Deep neural networks are known to have security issues. One particular threat is the Trojan attack. It occurs when the attackers stealthily manipulate the model's behavior through Trojaned training samples, which can later be exploited.…
A globally distributed IC supply chain brings risks due to untrusted third parties. The risks span inadvertent use of hardware Trojan (HT), inserted Intellectual Property (3P-IP) or Electronic Design Automation (EDA) flows. HT can introduce…
Machine learning has shown great promise in addressing several critical hardware security problems. In particular, researchers have developed novel graph neural network (GNN)-based techniques for detecting intellectual property (IP) piracy,…
Despite their success and popularity, deep neural networks (DNNs) are vulnerable when facing backdoor attacks. This impedes their wider adoption, especially in mission critical applications. This paper tackles the problem of Trojan…
Offshoring the proprietary Intellectual property (IP) has recently increased the threat of malicious logic insertion in the form of Hardware Trojan (HT). A potential and stealthy HT is triggered with nets that switch rarely during regular…
The use of third-party IP cores in implementing applications in FPGAs has given rise to the threat of malicious alterations through the insertion of hardware Trojans. To address this threat, it is important to predict the way hardware…