Intelligent financial fraud detection practices in post-pandemic era
The great losses caused by financial fraud have attracted continuous attention from
academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus …
academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus …
Adversarial attacks and defenses in machine learning-empowered communication systems and networks: A contemporary survey
Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …
been gaining significant attention due to the rapidly growing applications of deep learning in …
Privacy preserving vertical federated learning for tree-based models
Federated learning (FL) is an emerging paradigm that enables multiple organizations to
jointly train a model without revealing their private data to each other. This paper studies {\it …
jointly train a model without revealing their private data to each other. This paper studies {\it …
Artificial intelligence and fraud detection
Fraud exists in all walks of life and detecting and preventing fraud represents an important
research question relevant to many stakeholders in society. With the rise in big data and …
research question relevant to many stakeholders in society. With the rise in big data and …
Contrastive attributed network anomaly detection with data augmentation
Attributed networks are a type of graph structured data used in many real-world scenarios.
Detecting anomalies on attributed networks has a wide spectrum of applications such as …
Detecting anomalies on attributed networks has a wide spectrum of applications such as …
Fraud detection and prevention in e-commerce: A systematic literature review
VF Rodrigues, LM Policarpo, DE da Silveira… - Electronic Commerce …, 2022 - Elsevier
The high volume of money involved in e-commerce transactions draws the attention of
fraudsters, which makes fraud prevention and detection techniques of high importance …
fraudsters, which makes fraud prevention and detection techniques of high importance …
Squirrel: A Scalable Secure {Two-Party} Computation Framework for Training Gradient Boosting Decision Tree
Gradient Boosting Decision Tree (GBDT) and its variants are widely used in industry, due to
their high efficiency as well as strong interpretability. Secure multi-party computation allows …
their high efficiency as well as strong interpretability. Secure multi-party computation allows …
DP-TrajGAN: A privacy-aware trajectory generation model with differential privacy
Abstract Open Data Processing Services (ODPS) offers vast storage capacity and excellent
efficiency, which collects and stores a lot of data. As an essential component of ODPS …
efficiency, which collects and stores a lot of data. As an essential component of ODPS …
Secureboost+: A high performance gradient boosting tree framework for large scale vertical federated learning
Gradient boosting decision tree (GBDT) is a widely used ensemble algorithm in the industry.
Its vertical federated learning version, SecureBoost, is one of the most popular algorithms …
Its vertical federated learning version, SecureBoost, is one of the most popular algorithms …
xFraud: explainable fraud transaction detection
At online retail platforms, it is crucial to actively detect the risks of transactions to improve
customer experience and minimize financial loss. In this work, we propose xFraud, an …
customer experience and minimize financial loss. In this work, we propose xFraud, an …