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Changting Lin

ACL 2026×3INFOCOM 2026安全智能体与工具效率与系统可解释性评测与基准
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0 一作 · 4 篇 · ACL 2026 / INFOCOM 2026

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2026 顶会论文

4
作者位次 #4/5ACL 2026Findings· Findings of ACL

Silencing the Guardrails: Inference-Time Jailbreaking via Dynamic Contextual Representation Ablation

Wenpeng Xing · Moran Fang · Guangtai Wang · Changting Lin · Meng Han

摘要

While Large Language Models (LLMs) have achieved remarkable performance, they remain vulnerable to jailbreak attacks that circumvent safety constraints. Existing strategies, ranging from heuristic prompt engineering to computationally intensive optimization, often face significant trade-offs betw...

安全效率与系统可解释性OpenReview 项目页
作者位次 #7/9ACL 2026Findings· Findings of ACL

MCP -Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AI

Wenpeng Xing · Zhonghao Qi · Yupeng Qin · Yilin Li · Caini Chang · Jiahui Yu · Changting Lin · Zhenzhen Xie · Meng Han

摘要

While Large Language Models (LLMs) have achieved remarkable performance, they remain vulnerable to jailbreak. The integration of Large Language Models (LLMs) with external tools via protocols such as the Model Context Protocol (MCP) introduces critical security vulnerabilities, including prompt i...

安全评测与基准智能体与工具OpenReview 项目页
作者位次 #7/8ACL 2026Findings· Findings of ACL

Web Fraud Attacks Against LLM -Driven Multi-Agent Systems

Dezhang Kong · Hujin Peng · Yilun Zhang · Lele Zhao · Zhenhua Xu · Shi Lin · Changting Lin · Meng Han

摘要

With the proliferation of LLM-driven multi-agent systems (MAS), the security of Web links has become a critical concern. Once MAS is induced to trust a malicious link, attackers can use it as a springboard to expand the attack surface. In this paper, we propose Web Fraud Attacks, a novel type of...

安全智能体与工具长上下文与架构OpenReview 项目页

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