5 papers · 1 filter
SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks
Siyuan Li, Aodu Wulianghai, Zehao Liu +8
Large Language Models (LLMs) are increasingly deployed in interactive settings, where user intent commonly unfolds through multi-turn dialogue. Multi-turn jailbreaks exploit this p…
Stateful Cooperative Agents Safeguarding LLMs Against Evolving Multi-Turn Attacks
Siyuan Li, Zehao Liu, Haoyu Li +5
As LLMs become increasingly integrated into complex applications, their vulnerability to adversarial attacks has raised significant concerns. However, existing defenses remain reac…
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…
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…
Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devices
Hanqing Fu, Gaolei Li, Jun Wu +4
Federated neuromorphic learning (FedNL) leverages event-driven spiking neural networks and federated learning frameworks to effectively execute intelligent analysis tasks over amou…