Related papers: Defense-in-Depth: A Recipe for Logic Locking to Pr…

With the exponential rise in the use of cloud services, smart devices, and IoT devices, advanced cyber attacks have become increasingly sophisticated and ubiquitous. Furthermore, the rapid evolution of computing architectures and memory…

This work provides the community with a timely comprehensive review of backdoor attacks and countermeasures on deep learning. According to the attacker's capability and affected stage of the machine learning pipeline, the attack surfaces…

Large language models (LLMs) used across enterprises often use proprietary models and operate on sensitive inputs and data. The wide range of attack vectors identified in prior research - targeting various software and hardware components…

Secure Multi-Party Computation (MPC) is an important enabling technology for data privacy in modern distributed applications. Currently, proof methods for low-level MPC protocols are primarily manual and thus tedious and error-prone, and…

Defending large language models (LLMs) against jailbreak attacks is essential for their safe and reliable deployment. Existing defenses often rely on shallow pattern matching, which struggles to generalize to novel and unseen attack…

Recent years have witnessed the fast advance of security research for networked dynamical system (NDS). Considering the latest inference attacks that enable stealthy and precise attacks into NDSs with observation-based learning, this…

The transistors used to construct Integrated Circuits (ICs) continue to shrink. While this shrinkage improves performance and density, it also reduces trust: the price to build leading-edge fabrication facilities has skyrocketed, forcing…

To counter software reverse engineering or tampering, software obfuscation tools can be used. However, such tools to a large degree hard-code how the obfuscations are deployed. They hence lack resilience and stealth in the face of many…

This paper presents a high-level circuit obfuscation technique to prevent the theft of intellectual property (IP) of integrated circuits. In particular, our technique protects a class of circuits that relies on constant multiplications,…

Large Language Models (LLMs), while powerful, are built and trained to process a single text input. In common applications, multiple inputs can be processed by concatenating them together into a single stream of text. However, the LLM is…

Hardware intellectual property (IP) piracy is an emerging threat to the global supply chain. Correspondingly, various countermeasures aim to protect hardware IPs, such as logic locking, camouflaging, and split manufacturing. However, these…

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…

Model Inversion (MI) attacks pose a significant threat to the privacy of Deep Neural Networks by recovering training data distribution from well-trained models. While existing defenses often rely on regularization techniques to reduce…

With the rapid development of internet technologies, social networks, and other related areas, user authentication becomes more and more important to protect the data of users. Password authentication is one of the widely used methods to…

Circuit obfuscation is a frequently used approach to conceal logic functionalities in order to prevent reverse engineering attacks on fabricated chips. Efficient obfuscation implementations are expected with lower design complexity and…

There is growing adoption of smart devices such as digital locks with remote control and sophisticated authentication mechanisms. However, a lack of attention to device security and user-awareness beyond the primary function of these IoT…

Recent advancements in Large Language Model (LLM) safety have primarily focused on mitigating attacks crafted in natural language or common ciphers (e.g. Base64), which are likely integrated into newer models' safety training. However, we…

Keyloggers remain a serious threat in modern cybersecurity, silently capturing user keystrokes to steal credentials and sensitive information. Traditional defenses focus mainly on detection and removal, which can halt malicious activity but…

Protecting integrated circuits (ICs) from piracy and theft throughout their lifecycle is a persistent and complex challenge. In order to safeguard against illicit piracy attacks, this work proposes a novel framework utilizing Non-Fungible…

Large Language Models (LLMs) have emerged as a dominant approach for a wide range of NLP tasks, with their access to external information further enhancing their capabilities. However, this introduces new vulnerabilities, known as prompt…