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In this paper, we will demonstrate Hardware Trojan Attacks on four different digital designs implemented on FPGA. The hardware trojan is activated based on special logical and reduction-based operations on vectors which makes the…

Trojan backdoor is a poisoning attack against Neural Network (NN) classifiers in which adversaries try to exploit the (highly desirable) model reuse property to implant Trojans into model parameters for backdoor breaches through a poisoned…

In the evolving landscape of integrated circuit design, detecting Hardware Trojans (HTs) within a multi entity based design cycle presents significant challenges. This research proposes an innovative machine learning-based methodology for…

Not long ago, it was thought that only software applications and general purpose digital systems i.e. computers were prone to various types of attacks against their security. The underlying hardware, hardware implementations of these…

Recently, it has been shown that deep learning models are vulnerable to Trojan attacks, where an attacker can install a backdoor during training time to make the resultant model misidentify samples contaminated with a small trigger patch.…

The Hardware Trojan (HT) problem can be thought of as a continuous game between attackers and defenders, each striving to outsmart the other by leveraging any available means for an advantage. Machine Learning (ML) has recently played a key…

The globalization of the semiconductor industry has introduced security challenges to Integrated Circuits (ICs), particularly those related to the threat of Hardware Trojans (HTs) - malicious logic that can be introduced during IC…

Internet of Things (IoT) devices have become ubiquitous and are spread across many application domains including the industry, transportation, healthcare, and households. However, the proliferation of the IoT devices has raised the concerns…

The proliferation of the Internet and mobile devices has resulted in malicious bots access to genuine resources and data. Bots may instigate phishing, unauthorized access, denial-of-service, and spoofing attacks to mention a few.…

In the era of Internet of Things (IoT), Malware has been proliferating exponentially over the past decade. Traditional anti-virus software are ineffective against modern complex Malware. In order to address this challenge, researchers have…

AI models are often regarded as valuable intellectual property due to the high cost of their development, the competitive advantage they provide, and the proprietary techniques involved in their creation. As a result, AI model stealing…

As part of the revelations about the NSA activities, the notion of interdiction has become known to the public: the interception of deliveries to manipulate hardware in a way that backdoors are introduced. Manipulations can occur on the…

Trojan (backdoor) attack is a form of adversarial attack on deep neural networks where the attacker provides victims with a model trained/retrained on malicious data. The backdoor can be activated when a normal input is stamped with a…

An Air Force evaluation of Multics, and Ken Thompson's Turing award lecture ("Reflections on Trusting Trust"), showed that compilers can be subverted to insert malicious Trojan horses into critical software, including themselves. If this…

CAPTCHAs/HIPs are security mechanisms that try to prevent automatic abuse of services. They are susceptible to learning attacks in which attackers can use them as oracles. Kwon and Cha presented recently a novel algorithm that intends to…

Hardware Trojans (HT s) are a persistent threat to integrated circuits, especially when inserted at the register-transfer level (RTL). Existing methods typically first convert the design into a graph, such as a gate-level netlist or an…

Split manufacturing (SM) and layout camouflaging (LC) are two promising techniques to obscure integrated circuits (ICs) from malicious entities during and after manufacturing. While both techniques enable protecting the intellectual…

We present a Trojan (backdoor or trapdoor) attack that targets deep learning applications in wireless communications. A deep learning classifier is considered to classify wireless signals using raw (I/Q) samples as features and modulation…

Opaque predicates are a well-established fundamental building block for software obfuscation. Simplified, an opaque predicate implements an expression that provides constant Boolean output, but appears to have dynamic behavior for static…

In this paper, we take a deep dive into microarchitectural security from a hardware designer's perspective by reviewing the existing approaches to detect hardware vulnerabilities during the design phase. We show that a protection gap…