J Zhang, H Bu, H Wen, Y Chen, L Li, H Zhu - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid advancements in large language models (LLMs) have opened new avenues across various fields, including cybersecurity, which faces an ever-evolving threat landscape …
Automating hardware (HW) security vulnerability detection and mitigation during the design phase is imperative for two reasons:(i) It must be before chip fabrication, as post-fabrication …
The scarcity of comprehensive databases and bench-marks in hardware design specifically tailored for security tasks is a significant challenge in the community. Such databases are …
M Hassan, S Ahmadi-Pour, K Qayyum… - … , Automation & Test …, 2024 - ieeexplore.ieee.org
The increasing complexity of modern hardware designs poses significant challenges for design verification, particularly defining and verifying properties and invariants manually …
The recent progression of Large Language Models (LLMs) has witnessed great success in the fields of data-centric applications. LLMs trained on massive textual datasets showed …
This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across …
T Goto, K Ono, A Morita - Authorea Preprints, 2024 - techrxiv.org
This study presents a comprehensive evaluation of the cybersecurity robustness of five leading Large Language Models (LLMs)-ChatGPT-4, Google Gemini, Anthropic Claude …
R Kande, V Gohil, M DeLorenzo… - 2024 IEEE 42nd …, 2024 - ieeexplore.ieee.org
Large language models (LLMs) have emerged as transformative tools within the hardware design and verification lifecycle, offering numerous capabilities in accelerating design …
Contemporary methods for hardware security verification struggle with adaptability, scalability, and availability due to the increasing complexity of the modern system-on-chips …