42 citations · 106 across the 20 of their papers we have counts for
6 papers · 1 filter
Robust Fraud Detection via Supervised Contrastive Learning
Vinay M. S., Shuhan Yuan, Xintao Wu
Deep learning models have recently become popular for detecting malicious user activity sessions in computing platforms. In many real-world scenarios, only a few labeled malicious…
LogBERT: Log Anomaly Detection via BERT
Haixuan Guo, Shuhan Yuan, Xintao Wu
Detecting anomalous events in online computer systems is crucial to protect the systems from malicious attacks or malfunctions. System logs, which record detailed information of co…
Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities
Shuhan Yuan, Xintao Wu
Insider threats, as one type of the most challenging threats in cyberspace, usually cause significant loss to organizations. While the problem of insider threat detection has been…
Insider Threat Detection via Hierarchical Neural Temporal Point Processes
Shuhan Yuan, Panpan Zheng, Xintao Wu +1
Insiders usually cause significant losses to organizations and are hard to detect. Currently, various approaches have been proposed to achieve insider threat detection based on ana…
Spectrum-based deep neural networks for fraud detection
Shuhan Yuan, Xintao Wu, Jun Li +1
In this paper, we focus on fraud detection on a signed graph with only a small set of labeled training data. We propose a novel framework that combines deep neural networks and spe…
Wikipedia Vandal Early Detection: from User Behavior to User Embedding
Shuhan Yuan, Panpan Zheng, Xintao Wu +1
Wikipedia is the largest online encyclopedia that allows anyone to edit articles. In this paper, we propose the use of deep learning to detect vandals based on their edit history.…