39 citations · 133 across the 28 of their papers we have counts for
7 papers · 1 filter
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…
Boosting Pointer Analysis With LLM-Enhanced Allocation Function Detection
Baijun Cheng, Kailong Wang, Ling Shi +5
Pointer analysis is foundational for many static analysis tasks, yet its effectiveness is often hindered by imprecise modeling of heap allocations, particularly in C/C++ programs w…
Enhancing Semantic Understanding in Pointer Analysis using Large Language Models
Baijun Cheng, Kailong Wang, Ling Shi +4
Pointer analysis has been studied for over four decades. However, existing frameworks continue to suffer from the propagation of incorrect facts. A major limitation stems from thei…
GroupTuner: Efficient Group-Aware Compiler Auto-Tuning
Bingyu Gao, Mengyu Yao, Ziming Wang +4
Modern compilers typically provide hundreds of options to optimize program performance, but users often cannot fully leverage them due to the huge number of options. While standard…
No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection
Yi Huang, Shaofei Li, Yao Guo +3
Provenance graph analysis plays a vital role in intrusion detection, particularly against Advanced Persistent Threats (APTs), by exposing complex attack patterns. While recent syst…
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…