4 papers · 1 filter
Inverting the Hidden: Unveiling Multimodal Privacy Leakage in Collaborative LVLM Inference
Shuaifan Jin, Zhibo Wang, Qiyuan Wang +5
Collaborative inference deploys Large Vision-Language Models (LVLMs) by partitioning computation between edge devices and the cloud. While withholding raw inputs supposedly ensures…
DualSentinel: A Lightweight Framework for Detecting Targeted Attacks in Black-box LLM via Dual Entropy Lull Pattern
Xiaoyi Pang, Xuanyi Hao, Pengyu Liu +3
Recent intelligent systems integrate powerful Large Language Models (LLMs) through APIs, but their trustworthiness may be critically undermined by targeted attacks like backdoor an…
Privacy-Preserving LLM Embedding Transmission for End-Cloud Collaboration
Shuaifan Jin, Xiaoyi Pang, Zhibo Wang +4
Recent studies improve on-device language model (LM) inference through end-cloud collaboration, where the end device retrieves useful information from cloud databases to enhance lo…
Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning
Zhibo Wang, Zhiwei Chang, Jiahui Hu +4
Federated Learning (FL) exhibits privacy vulnerabilities under gradient inversion attacks (GIAs), which can extract private information from individual gradients. To enhance privac…