activity
20172019
most citedOne-Class Adversarial Nets for Fraud Detection

11 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2019★ 2 cited

Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process

Panpan Zheng, Shuhan Yuan, Xintao Wu +1

The darknet markets are notorious black markets in cyberspace, which involve selling or brokering drugs, weapons, stolen credit cards, and other illicit goods. To combat illicit tr…

cs.CR2019★ 6 cited

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…

cs.LG2018

SAFE: A Neural Survival Analysis Model for Fraud Early Detection

Panpan Zheng, Shuhan Yuan, Xintao Wu

Many online platforms have deployed anti-fraud systems to detect and prevent fraudulent activities. However, there is usually a gap between the time that a user commits a fraudulen…

cs.LG2018★ 11 cited

One-Class Adversarial Nets for Fraud Detection

Panpan Zheng, Shuhan Yuan, Xintao Wu +2

Many online applications, such as online social networks or knowledge bases, are often attacked by malicious users who commit different types of actions such as vandalism on Wikipe…

cs.CR2017★ 7 cited

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.…