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20242026
most citedA Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures

2 citations · 2 across the 14 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CV2025

Scalpel-SAM: A Semi-Supervised Paradigm for Adapting SAM to Infrared Small Object Detection

Zihan Liu, Xiangning Ren, Dezhang Kong +2

Infrared small object detection urgently requires semi-supervised paradigms due to the high cost of annotation. However, existing methods like SAM face significant challenges of do…

cs.CR2025

Web Fraud Attacks Against LLM-Driven Multi-Agent Systems

Dezhang Kong, Hujin Peng, Yilun Zhang +5

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 ca…

cs.CR2025

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends

Zhenhua Xu, Xubin Yue, Zhebo Wang +9

Copyright protection for large language models is of critical importance, given their substantial development costs, proprietary value, and potential for misuse. Existing surveys h…

cs.CR2025★ 2 cited

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures

Dezhang Kong, Shi Lin, Zhenhua Xu +16

In recent years, Large-Language-Model-driven AI agents have exhibited unprecedented intelligence and adaptability. Nowadays, agents are undergoing a new round of evolution. They no…

cs.LG2025

NeuRel-Attack: Neuron Relearning for Safety Disalignment in Large Language Models

Yi Zhou, Wenpeng Xing, Dezhang Kong +2

Safety alignment in large language models (LLMs) is achieved through fine-tuning mechanisms that regulate neuron activations to suppress harmful content. In this work, we propose a…