activity
20232026
most citedLLM4SecHW: Leveraging Domain Specific Large Language Model for Hardware Debugging

45 citations · 46 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

BlindMarket: Enabling Verifiable, Confidential, and Traceable IP Core Distribution in Zero-Trust Settings

Zhaoxiang Liu, Samuel Judson, Raj Dutta +3

We present BlindMarket, an end-to-end zero-trust distribution framework for hardware IP cores. BlindMarket allows two parties, the IP user and the IP vendor, to complete an IP trad…

quant-ph2024★ 1 cited

Multi-Stage Watermarking for Quantum Circuits

Min Yang, Xiaolong Guo, Lei Jiang

Quantum computing represents a burgeoning computational paradigm that significantly advances the resolution of contemporary intricate problems across various domains, including cry…

cs.AR2024★ 45 cited

LLM4SecHW: Leveraging Domain Specific Large Language Model for Hardware Debugging

Weimin Fu, Kaichen Yang, Raj Gautam Dutta +2

This paper presents LLM4SecHW, a novel framework for hardware debugging that leverages domain specific Large Language Model (LLM). Despite the success of LLMs in automating various…

cs.CR2023

HeisenTrojans: They Are Not There Until They Are Triggered

Akshita Reddy Mavurapu, Haoqi Shan, Xiaolong Guo +2

The hardware security community has made significant advances in detecting Hardware Trojan vulnerabilities using software fuzzing-inspired automated analysis. However, the Electron…

cs.AR2023

VGF: Value-Guided Fuzzing -- Fuzzing Hardware as Hardware

Ruochen Dai, Michael Lee, Patrick Hoey +6

As the complexity of logic designs increase, new avenues for testing digital hardware becomes necessary. Fuzz Testing (fuzzing) has recently received attention as a potential candi…