8 citations · 19 across the 19 of their papers we have counts for
13 papers · 1 filter
Description-Code Inconsistency in Real-world MCP Servers: Measurement, Detection, and Security Implications
Yutao Shi, Xiaohan Zhang, Xiangjing Zhang +5
The Model Context Protocol (MCP) has emerged as a critical standard empowering Large Language Models (LLMs) to utilize external tools. In this ecosystem, LLMs rely on natural langu…
A First Measurement Study on Authentication Security in Real-World Remote MCP Servers
Huijun Zhou, Xiaohan Zhang, Haozhe Zhang +3
The Model Context Protocol (MCP) is emerging as a common interface connecting large language models (LLMs) with external services. Remote deployments are becoming increasingly impo…
Unveiling the Resilience of LLM-Enhanced Search Engines against Black-Hat SEO Manipulation
Pei Chen, Geng Hong, Xinyi Wu +6
The emergence of Large Language Model-enhanced Search Engines (LLMSEs) has revolutionized information retrieval by integrating web-scale search capabilities with AI-powered summari…
Safe Text-to-Image Generation: Simply Sanitize the Prompt Embedding
Huming Qiu, Guanxu Chen, Mi Zhang +3
In recent years, text-to-image (T2I) generation models have made significant progress in generating high-quality images that align with text descriptions. However, these models als…
No-Skim: Towards Efficiency Robustness Evaluation on Skimming-based Language Models
Shengyao Zhang, Mi Zhang, Xudong Pan +1
To reduce the computation cost and the energy consumption in large language models (LLM), skimming-based acceleration dynamically drops unimportant tokens of the input sequence pro…
BELT: Old-School Backdoor Attacks can Evade the State-of-the-Art Defense with Backdoor Exclusivity Lifting
Huming Qiu, Junjie Sun, Mi Zhang +2
Deep neural networks (DNNs) are susceptible to backdoor attacks, where malicious functionality is embedded to allow attackers to trigger incorrect classifications. Old-school backd…