4 papers
HoneyTrap: Deceiving Large Language Model Attackers to Honeypot Traps with Resilient Multi-Agent Defense
Siyuan Li, Xi Lin, Jun Wu +5
Jailbreak attacks pose significant threats to large language models (LLMs), enabling attackers to bypass safeguards. However, existing reactive defense approaches struggle to keep…
StyleDecipher: Robust and Explainable Detection of LLM-Generated Texts with Stylistic Analysis
Siyuan Li, Aodu Wulianghai, Xi Lin +4
With the increasing integration of large language models (LLMs) into open-domain writing, detecting machine-generated text has become a critical task for ensuring content authentic…
Model-Agnostic Sentiment Distribution Stability Analysis for Robust LLM-Generated Texts Detection
Siyuan Li, Xi Lin, Guangyan Li +5
The rapid advancement of large language models (LLMs) has resulted in increasingly sophisticated AI-generated content, posing significant challenges in distinguishing LLM-generated…
BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems
Andy K. Zhang, Joey Ji, Celeste Menders +31
AI agents have the potential to significantly alter the cybersecurity landscape. Here, we introduce the first framework to capture offensive and defensive cyber-capabilities in evo…