SV-LLM automates SoC security verification with six cooperating LLM agents, reaching 84.8% vulnerability detection accuracy and 82% to 89% bug validation rates on benchmarks the paper does not disclose.
Riscvuzz: Discovering architectural cpu vulnerabilities via differential hardware fuzzing,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CR 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models
SV-LLM automates SoC security verification with six cooperating LLM agents, reaching 84.8% vulnerability detection accuracy and 82% to 89% bug validation rates on benchmarks the paper does not disclose.