Related papers: TrojanLoC: LLM-based Framework for RTL Trojan Loca…

Large Language Models (LLMs) have achieved remarkable success in generative tasks, including register-transfer level (RTL) hardware synthesis. However, their tendency to memorize training data poses critical risks when proprietary or…

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…

Register-Transfer Level (RTL) synthesis and summarization are central to hardware design automation but remain challenging for Large Language Models (LLMs) due to rigid HDL syntax, limited supervision, and weak alignment with natural…

Hardware Trojans have drawn the attention of academia, industry and government agencies. Effective detection mechanisms and countermeasures against such malicious designs can only be developed when there is a deep understanding of how…

The advanced complex electronic systems increasingly demand safer and more secure hardware parts. Correspondingly, fault injection became a major verification milestone for both safety- and security-critical applications. However, fault…

In today's interconnected digital landscape, the proliferation of malware poses a significant threat to the security and stability of computer networks and systems worldwide. As the complexity of malicious tactics, techniques, and…

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…

Self-supervised learning (SSL) is a prevalent approach for encoding data representations. Using a pre-trained SSL image encoder and subsequently training a downstream classifier, impressive performance can be achieved on various tasks with…

Single-molecule localization microscopy (SMLM) surpasses the diffraction limit, achieving subcellular resolution. Traditional SMLM analysis methods often rely on point spread function (PSF) model fitting, limiting the application of complex…

As Large Language Models (LLMs) become integral to computing infrastructure, safety alignment serves as the primary security control preventing the generation of harmful payloads. However, this defense remains brittle. Existing jailbreak…

Network intrusions are a significant problem in all industries today. A critical part of the solution is being able to effectively detect intrusions. With recent advances in artificial intelligence, current research has begun adopting deep…

Neural networks can conceal malicious Trojan backdoors that allow a trigger to covertly change the model behavior. Detecting signs of these backdoors, particularly without access to any triggered data, is the subject of ongoing research and…

Spectral Graph Neural Networks (SGNNs) have achieved remarkable performance in tasks such as node classification due to their ability to learn flexible filters. Typically, these filters are learned under the supervision of downstream tasks,…

This paper proposes a novel method for tamper detection and recovery using semi-fragile data hiding, based on Lifting Wavelet Transform (LWT) and Feed-Forward Neural Network (FNN). In TRLF, first, the host image is decomposed up to one…

LLM post-training typically propagates task gradients through the full depth of the model. Although this end-to-end structure is simple and general, it couples task adaptation to full-depth activation storage, long-range backward…

Software developers frequently hard-code credentials such as passwords, generic secrets, private keys, and generic tokens in software repositories, even though it is strictly advised against due to the severe threat to the security of the…

LLM-based RTL generation is an interesting research direction, as it holds the potential to liberate the least automated stage in the current chip design. However, due to the substantial semantic gap between high-level specifications and…

Side-channel analysis has been proven effective at detecting hardware Trojans in integrated circuits (ICs). However, most detection techniques rely on large external probes and antennas for data collection and require a long measurement…

Always-on hardware Trojans (HTs) pose a critical risk to trusted microelectronics, yet most side-channel detection methods rely on unavailable golden references. We present a reference-free approach that combines time-frequency EM analysis…

In modern VLSI design flow, the register-transfer level (RTL) stage is a critical point, where designers define precise design behavior with hardware description languages (HDLs) like Verilog. Since the RTL design is in the format of HDL…