6 papers · 1 filter
VirusCascade: Hijacking Collaborative Reflection in LLM-Powered Recommender Agents
Yurong Hao, Wen Zhou, Guowei Guan +3
Advancing beyond traditional static scoring models, LLM-powered agentic recommender systems (LLM-ARS) instantiate users and items as autonomous agents, whose semantic states are dy…
SynChain: Inducing Computer-Use Agent Systems to Construct Their Own Attack Chains
Fuyao Zhang, Jiaming Zhang, Che Wang +7
Computer-use agents~(CUAs) have transformed large language models into persistent execution systems capable of generating, storing, and reusing artifacts like skills and memory ent…
VENOMREC: Cross-Modal Interactive Poisoning for Targeted Promotion in Multimodal LLM Recommender Systems
Guowei Guan, Yurong Hao, Jiaming Zhang +6
Multimodal large language models (MLLMs) are pushing recommender systems (RecSys) toward content-grounded retrieval and ranking via cross-modal fusion. We find that while cross-mod…
DualTAP: A Dual-Task Adversarial Protector for Mobile MLLM Agents
Fuyao Zhang, Jiaming Zhang, Che Wang +6
The reliance of mobile GUI agents on Multimodal Large Language Models (MLLMs) introduces a severe privacy vulnerability: screenshots containing Personally Identifiable Information…
Spattack: Subgroup Poisoning Attacks on Federated Recommender Systems
Bo Yan, Yurong Hao, Dingqi Liu +5
Federated recommender systems (FedRec) have emerged as a promising approach to provide personalized recommendations while protecting user privacy. However, recent studies have show…
Verifiably Forgotten? Gradient Differences Still Enable Data Reconstruction in Federated Unlearning
Fuyao Zhang, Wenjie Li, Yurong Hao +3
Federated Unlearning (FU) has emerged as a critical compliance mechanism for data privacy regulations, requiring unlearned clients to provide verifiable Proof of Federated Unlearni…