5 citations · 7 across the 9 of their papers we have counts for
11 papers
VeriRouter: Towards Verifiable LLM Routing
Mengyu Yao, Ziqi Zhang, Shaofei Li +4
Large language model (LLM) routers are increasingly deployed to optimize quality, latency, and cost through dynamic model selection and request rewriting. However, a compromised ro…
Connect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation Systems
Mengyu Yao, Ziqi Zhang, Ning Luo +5
Stealing attacks pose a persistent threat to the intellectual property of deployed machine-learning systems. Retrieval-augmented generation (RAG) intensifies this risk by extending…
Who Grants the Agent Power? Defending Against Instruction Injection via Task-Centric Access Control
Yifeng Cai, Ziming Wang, Zhaomeng Deng +6
AI agents capable of GUI understanding and Model Context Protocol are increasingly deployed to automate mobile tasks. However, their reliance on over-privileged, static permissions…
Who Moved My Transaction? Uncovering Post-Transaction Auditability Vulnerabilities in Modern Super Apps
Junlin Liu, Zhaomeng Deng, Ziming Wang +6
Super apps are the cornerstones of modern digital life, embedding financial transactions into nearly every aspect of daily routine. The prevailing security paradigm for these platf…
PromoGuardian: Detecting Promotion Abuse Fraud with Multi-Relation Fused Graph Neural Networks
Shaofei Li, Xiao Han, Ziqi Zhang +6
As e-commerce platforms develop, fraudulent activities are increasingly emerging, posing significant threats to the security and stability of these platforms. Promotion abuse is on…
I Can Tell Your Secrets: Inferring Privacy Attributes from Mini-app Interaction History in Super-apps
Yifeng Cai, Ziqi Zhang, Mengyu Yao +8
Super-apps have emerged as comprehensive platforms integrating various mini-apps to provide diverse services. While super-apps offer convenience and enriched functionality, they ca…
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models
Yifeng Cai, Ziqi Zhang, Ding Li +2
Modern Federated Learning (FL) has become increasingly essential for handling highly heterogeneous mobile devices. Current approaches adopt a partial model aggregation paradigm tha…
Interference-free Operating System: A 6 Years' Experience in Mitigating Cross-Core Interference in Linux
Zhaomeng Deng, Ziqi Zhang, Ding Li +5
Real-time operating systems employ spatial and temporal isolation to guarantee predictability and schedulability of real-time systems on multi-core processors. Any unbounded and un…
TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Models
Ding Li, Ziqi Zhang, Mengyu Yao +3
Trusted Execution Environments (TEE) are used to safeguard on-device models. However, directly employing TEEs to secure the entire DNN model is challenging due to the limited compu…
Query Provenance Analysis: Efficient and Robust Defense against Query-based Black-box Attacks
Shaofei Li, Ziqi Zhang, Haomin Jia +3
Query-based black-box attacks have emerged as a significant threat to machine learning systems, where adversaries can manipulate the input queries to generate adversarial examples…
No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML
Ziqi Zhang, Chen Gong, Yifeng Cai +5
On-device ML introduces new security challenges: DNN models become white-box accessible to device users. Based on white-box information, adversaries can conduct effective model ste…