3 papers
cs.CR2026
SysEvolve: An AI-native, safe, autonomous adversarial attack-defense co-evolutionary system
Yuhan Meng, Shaofei Li, Jionghao Huang +8
The rapid advancement of large language models (LLMs) has created a growing asymmetry in cybersecurity, where attack accelerates toward autonomous execution while defense remains p…
cs.OS2025
Trustworthy and Controllable Professional Knowledge Utilization in Large Language Models with TEE-GPU Execution
Yifeng Cai, Zhida An, Yuhan Meng +5
Future improvements in large language model (LLM) services increasingly hinge on access to high-value professional knowledge rather than more generic web data. However, the data pr…
cs.CR2025
KnowHow: Automatically Applying High-Level CTI Knowledge for Interpretable and Accurate Provenance Analysis
Yuhan Meng, Shaofei Li, Jiaping Gui +2
High-level natural language knowledge in CTI reports, such as the ATT&CK framework, is beneficial to counter APT attacks. However, how to automatically apply the high-level knowled…