Showing 1–20 of 30 results
/ Date/ Name
Aug 6, 2018Automated Extraction of Personal Knowledge from Smartphone Push NotificationsNov 29, 2018Traffic Danger Recognition With Surveillance Cameras Without Training DataJan 9, 2019Humanoid: A Deep Learning-based Approach to Automated Black-box Android App TestingJul 19, 2022A Survey on EOSIO Systems Security: Vulnerability, Attack, and MitigationNov 4, 2023NODLINK: An Online System for Fine-Grained APT Attack Detection and InvestigationMay 31, 2024Query Provenance Analysis: Efficient and Robust Defense against Query-based Black-box AttacksJun 6, 2025No Data? No Problem: Synthesizing Security Graphs for Better Intrusion DetectionMar 2, 2021TransTailor: Pruning the Pre-trained Model for Improved Transfer LearningMar 2, 2021PFA: Privacy-preserving Federated Adaptation for Effective Model PersonalizationJul 29, 2023Auditing Frameworks Need Resource Isolation: A Systematic Study on the Super Producer Threat to System Auditing and Its MitigationMay 13, 2025GroupTuner: Efficient Group-Aware Compiler Auto-TuningOct 13, 2020S3ML: A Secure Serving System for Machine Learning InferenceJul 17, 2023Are we there yet? An Industrial Viewpoint on Provenance-based Endpoint Detection and Response ToolsApr 14, 2023Eunomia: Enabling User-specified Fine-Grained Search in Symbolically Executing WebAssembly BinariesOct 14, 2025PromoGuardian: Detecting Promotion Abuse Fraud with Multi-Relation Fused Graph Neural NetworksMar 13, 2025Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous ModelsAug 29, 2025Enhancing Semantic Understanding in Pointer Analysis using Large Language ModelsOct 11, 2023No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device MLMar 23, 2020Adversarial Attacks on Monocular Depth EstimationNov 15, 2024TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Models