activity
20242026
most citedEMPalm: Exfiltrating Palm Biometric Data via Electromagnetic Side-Channel

2 citations · 2 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CR2026

Can Agents Trust Their Skills? Uncovering Unsafe Chains of Trust in Skill-Based LLM Agents

Yan Wang, Zhihao Zhang, Ke Chen +5

LLM agents increasingly rely on installable skills, which are packages of instructions, code, and resources that equip them with task-specific capabilities and, once installed, can…

cs.CR2026

LoRango: It Takes Two LoRAs to Unlock Hidden Behaviors in Diffusion Models

Jin Wei, Rundong Li, Ruihao Yang +10

Users commonly combine multiple Low-Rank Adaptation (LoRA) adapters to personalize images with different subjects, styles, and visual attributes. Yet inspecting adapters individual…

cs.CR2026

A Trustworthy Watermarking Framework for LLM-Generated Food Safety Content

Zhongli Fang, Yiran Chen, Lingyun Zhang +4

Large language models are transforming many industries with their text generation abilities. However, their outputs can be easily tampered with, creating serious risks in critical…

cs.CL2026

Measuring the Wrong Thing: Internal Harmfulness Scores Anti-Rank Successful Jailbreaks

Mingyu Luo, Ming Deng, Zilang Qiu +8

Internal safety scores judge a prompt before any text is generated, and they are validated by how well they separate harmful prompts from benign ones. That separation is then read…

cs.CR2026

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems

Haowen Xu, Xue Tan, Lei Ma +6

While enabling effective collaboration on complex tasks, LLM-based Multi-Agent Systems (MAS) face critical security challenges due to vulnerabilities at the agent and interaction l…

cs.IR2026

PRA-RAG: Provably Robust Aggregation in Retrieval-Augmented Generation against Retrieval Corruption

Xue Tan, Yi Zheng, Chang Huo +7

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge, effectively mitigating their inherent knowledge limitations. However…

cs.CR2026

Generalizable and Interpretable RF Fingerprinting with Shapelet-Enhanced Large Language Models

Tianya Zhao, Junqing Zhang, Haowen Xu +3

Deep neural networks (DNNs) have achieved remarkable success in radio frequency (RF) fingerprinting for wireless device authentication. However, their practical deployment faces tw…

cs.CR2025★ 2 cited

EMPalm: Exfiltrating Palm Biometric Data via Electromagnetic Side-Channel

Haowen Xu, Tianya Zhao, Xuyu Wang +4

Palm recognition has emerged as a dominant biometric authentication technology in critical infrastructure. These systems operate in either single-modal form, using palmprint or pal…

cs.CR2024

RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis

Xue Tan, Hao Luan, Mingyu Luo +3

Retrieval-Augmented Generation (RAG) enriches the input to LLMs by retrieving information from the relevant knowledge database, enabling them to produce responses that are more acc…

cs.CR2024

Enabling Practical and Privacy-Preserving Image Processing

Chao Wang, Shubing Yang, Xiaoyan Sun +2

Fully Homomorphic Encryption (FHE) enables computations on encrypted data, preserving confidentiality without the need for decryption. However, FHE is often hindered by significant…

cs.CR2024

HuntFUZZ: Enhancing Error Handling Testing through Clustering Based Fuzzing

Jin Wei, Ping Chen, Jun Dai +4

Testing a program's capability to effectively handling errors is a significant challenge, given that program errors are relatively uncommon. To solve this, Software Fault Injection…

cs.CR2024

SQLaser: Detecting DBMS Logic Bugs with Clause-Guided Fuzzing

Jin Wei, Ping Chen, Kangjie Lu +2

Database Management Systems (DBMSs) are vital components in modern data-driven systems. Their complexity often leads to logic bugs, which are implementation errors within the DBMSs…