Related papers: Hardware Trojan Detection Using Unsupervised Deep …

The Quantum Diamond Microscope (QDM) is an instrument with a demonstrated capability to image electrical current in integrated circuits (ICs), which shows promise for detection of hardware Trojans. The anomalous current activity caused by…

The risk of hardware Trojans being inserted at various stages of chip production has increased in a zero-trust fabless era. To counter this, various machine learning solutions have been developed for the detection of hardware Trojans. While…

With the globalization of the semiconductor manufacturing process, electronic devices are powerless against malicious modification of hardware in the supply chain. The ever-increasing threat of hardware Trojan attacks against integrated…

Hardware Trojan detection and protection is becoming more crucial as more untrusted third parties manufacture many parts of critical systems nowadays. The most common way to detect hardware Trojans is comparing the untrusted design with a…

Current density distributions in active integrated circuits (ICs) result in patterns of magnetic fields that contain structural and functional information about the IC. Magnetic fields pass through standard materials used by the…

As the semiconductor industry has shifted to a fabless paradigm, the risk of hardware Trojans being inserted at various stages of production has also increased. Recently, there has been a growing trend toward the use of machine learning…

As integrated circuit (IC) geometry and packaging become more sophisticated with ongoing fabrication and design innovations, the electrical engineering community needs increasingly-powerful failure analysis (FA) methods to meet the growing…

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…

Cyber-physical systems rely on sensors, communication, and computing, all powered by integrated circuits (ICs). ICs are largely susceptible to various hardware attacks with malicious intents. One of the stealthiest threats is the insertion…

The globalization of the Integrated Circuit (IC) supply chain has moved most of the design, fabrication, and testing process from a single trusted entity to various untrusted third-party entities around the world. The risk of using…

The quantum diamond microscope (QDM) is a recently developed technology for near-field imaging of magnetic fields with micron-scale spatial resolution. In the present work, we integrate a QDM with a narrowband measurement protocol and a…

Hardware trojan detection methods, based on machine learning (ML) techniques, mainly identify suspected circuits but lack the ability to explain how the decision was arrived at. An explainable methodology and architecture is introduced…

Machine learning models that use deep neural networks (DNNs) are vulnerable to backdoor attacks. An adversary carrying out a backdoor attack embeds a predefined perturbation called a trigger into a small subset of input samples and trains…

We provide an overview of the experimental techniques, measurement modalities, and diverse applications of the Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) color centers near the…

There are increasing concerns about possible malicious modifications of integrated circuits (ICs) used in critical applications. Such attacks are often referred to as hardware Trojans. While many techniques focus on hardware Trojan…

This paper reports a novel approach that uses transistor aging in an integrated circuit (IC) to detect hardware Trojans. When a transistor is aged, it results in delays along several paths of the IC. This increase in delay results in timing…

Deep neural networks have been shown to be vulnerable to backdoor, or trojan, attacks where an adversary has embedded a trigger in the network at training time such that the model correctly classifies all standard inputs, but generates a…

The Quantum Diamond Microscope (QDM) is an emerging magnetic imaging tool enabling noninvasive characterization of electronic circuits through spatially mapping current densities. In this work, we demonstrate wafer-level current sensing of…

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…

An image encoder pre-trained by self-supervised learning can be used as a general-purpose feature extractor to build downstream classifiers for various downstream tasks. However, many studies showed that an attacker can embed a trojan into…