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cs.CR2026

Understanding Implicit Trust Errors in Core Carrier Networks through Multi-Agent Flaw Discovery and Analysis

Ziyu Lin, Ziting Wang, Xinfeng Li +2

Cellular core networks (CNs) are critical infrastructure, yet their internal security model has historically relied on physical isolation: interfaces between core components often…

cs.CR2026

The Landscape of Prompt Injection Threats in LLM Agents: From Taxonomy to Analysis

Peiran Wang, Xinfeng Li, Chong Xiang +5

The evolution of Large Language Models (LLMs) has resulted in a paradigm shift towards autonomous agents, necessitating robust security against Prompt Injection (PI) vulnerabilitie…

cs.CR2026

DP-MGTD: Privacy-Preserving Machine-Generated Text Detection via Adaptive Differentially Private Entity Sanitization

Lionel Z. Wang, Yusheng Zhao, Jiabin Luo +6

The deployment of Machine-Generated Text (MGT) detection systems necessitates processing sensitive user data, creating a fundamental conflict between authorship verification and pr…

cs.CR2025

EmoRAG: Evaluating RAG Robustness to Symbolic Perturbations

Xinyun Zhou, Xinfeng Li, Yinan Peng +9

Retrieval-Augmented Generation (RAG) systems are increasingly central to robust AI, enhancing large language model (LLM) faithfulness by incorporating external knowledge. However,…

cs.CR2025

A-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory

Qianshan Wei, Tengchao Yang, Yaochen Wang +7

Large Language Model (LLM) agents use memory to learn from past interactions, enabling autonomous planning and decision-making in complex environments. However, this reliance on me…

cs.CR2025

The Man Behind the Sound: Demystifying Audio Private Attribute Profiling via Multimodal Large Language Model Agents

Lixu Wang, Kaixiang Yao, Xinfeng Li +4

Our research uncovers a novel privacy risk associated with multimodal large language models (MLLMs): the ability to infer sensitive personal attributes from audio data -- a techniq…