2 papers
cs.CR2026
When Label Noise Meets Class Imbalance: A Robust Framework for Android Malware Family Classification
Haolan Zhang, Cuiying Gao, Fulin Zhao +6
Machine learning methods for Android malware family classification have achieved high accuracy, but their application is hindered by two major challenges. First, the widely used co…
cs.CR2026
When Agents See Differently: Exposing UI Desynchronization Threats in Mobile Agents
Heng Li, Fulin Zhao, Zhe Geng +3
Mobile agents are increasingly capable of autonomously interacting with mobile applications and performing consequential actions on behalf of users. Effective human oversight of su…