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Backdoor (trojan) attacks embed hidden, controllable behaviors into machine-learning models so that models behave normally on benign inputs but produce attacker-chosen outputs when a trigger is present. This survey reviews the rapidly…

This article deals with the IT security of connectionist artificial intelligence (AI) applications, focusing on threats to integrity, one of the three IT security goals. Such threats are for instance most relevant in prominent AI computer…

Intellectual Property (IP) infringement including piracy and over production have emerged as significant threats in the semiconductor supply chain. Key based obfuscation techniques (i.e., logic locking) are widely applied to secure legacy…

Password users frequently employ passwords that are too simple, or they just reuse passwords for multiple websites. A common complaint is that utilizing secure passwords is too difficult. One possible solution to this problem is to use a…

Making classifiers robust to adversarial examples is hard. Thus, many defenses tackle the seemingly easier task of detecting perturbed inputs. We show a barrier towards this goal. We prove a general hardness reduction between detection and…

Audio CAPTCHAs are supposed to provide a strong defense for online resources; however, advances in speech-to-text mechanisms have rendered these defenses ineffective. Audio CAPTCHAs cannot simply be abandoned, as they are specifically named…

Recent results have shown the usefulness of tamper-proof hardware tokens as a setup assumption for building UC-secure two-party computation protocols, thus providing broad security guarantees and allowing the use of such protocols as…

This article attempts to create a software and hardware complex that can work autonomously and demonstrates the ease of implementation of attacks on denial of service on wireless networks, which in turn emphasizes the need to provide…

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…

A variety of defenses have been proposed against Trojans planted in (backdoor attacks on) deep neural network (DNN) classifiers. Backdoor-agnostic methods seek to reliably detect and/or to mitigate backdoors irrespective of the…

Encryption-based cyber threats continue to evolve, leveraging increasingly sophisticated cryptographic techniques to evade detection and persist within compromised systems. A hierarchical classification framework designed to analyze…

Frontier artificial intelligence (AI) systems pose increasing risks to society, making it essential for developers to provide assurances about their safety. One approach to offering such assurances is through a safety case: a structured,…

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…

Existing methods for verifying access control policies require the policy to be complete and fully determined before verification can proceed, but in practice policies are developed iteratively, composed from independently maintained…

Over recent years, devising classification algorithms that are robust to adversarial perturbations has emerged as a challenging problem. In particular, deep neural nets (DNNs) seem to be susceptible to small imperceptible changes over test…

Resource constrained Internet-of-Things (IoT) devices are highly likely to be compromised by attackers because strong security protections may not be suitable to be deployed. This requires an alternative approach to protect vulnerable…

Commercial Off-The-Shelf (COTS) hardware, such as microprocessors, are widely adopted in system design due to their ability to reduce development time and cost compared to custom solutions. However, supply chain entities involved in the…

The ability to deploy neural networks in real-world, safety-critical systems is severely limited by the presence of adversarial examples: slightly perturbed inputs that are misclassified by the network. In recent years, several techniques…

Distributed network of the computer and the design defects of the TCP protocol are given to the network attack to be multiplicative. Based on the simple and open assumptions of the TCP protocol in academic and collaborative communication…

The growing use of third-party hardware accelerators (e.g., FPGAs, ASICs) for deep neural networks (DNNs) introduces new security vulnerabilities. Conventional model-level backdoor attacks, which only poison a model's weights to misclassify…