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Financial Fraud Detection using Deep Support Vector Data Description

https://doi.org/10.1109/bigdata50022.2020.9378256

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-27400-3_11openalex-snapshot

Modeling Insurance Fraud Detection Using Imbalanced Data Classification

inferredcites →https://doi.org/10.1007/978-3-319-46675-0_53openalex-snapshot

Credit Card Fraud Detection Using Convolutional Neural Networks

inferredcites →https://doi.org/10.1007/s41060-018-0116-zopenalex-snapshot

Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization

inferredcites →https://doi.org/10.1016/j.comcom.2020.05.048openalex-snapshot

An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture

inferredcites →https://doi.org/10.1016/j.eswa.2018.01.037openalex-snapshot

Sequence classification for credit-card fraud detection

inferredcites →https://doi.org/10.1016/j.future.2019.08.029openalex-snapshot

Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs

inferredcites →https://doi.org/10.1016/j.ins.2017.12.030openalex-snapshot

Using generative adversarial networks for improving classification effectiveness in credit card fraud detection

inferredcites →https://doi.org/10.1016/j.neucom.2011.02.021openalex-snapshot

Improved competitive learning neural networks for network intrusion and fraud detection

inferredcites →https://doi.org/10.1109/aeeicb.2017.7972424openalex-snapshot

Analysis on credit card fraud identification techniques based on KNN and outlier detection

inferredcites →https://doi.org/10.1109/hpcc/smartcity/dss.2019.00249openalex-snapshot

A Hierarchical Clustering Strategy of Processing Class Imbalance and Its Application in Fraud Detection

inferredcites →https://doi.org/10.1109/icnsc.2018.8361343openalex-snapshot

Random forest for credit card fraud detection

inferredcites →https://doi.org/10.1109/sieds.2018.8374722openalex-snapshot

Deep learning detecting fraud in credit card transactions

inferredcites →https://doi.org/10.1109/trustcom.2015.535openalex-snapshot

From ZeuS to Zitmo: Trends in Banking Malware

inferredcites →https://doi.org/10.1145/3352411.3352433openalex-snapshot

A Behavior-cluster Based Imbalanced Classification Method for Credit Card Fraud Detection

inferredcites →https://doi.org/10.1155/2018/5680264openalex-snapshot

A Model Based on Convolutional Neural Network for Online Transaction Fraud Detection

inferredcites →https://doi.org/10.14569/ijacsa.2018.090103openalex-snapshot

Credit Card Fraud Detection using Deep Learning based on Auto-Encoder and Restricted Boltzmann Machine

inferredcites →https://doi.org/10.48550/arxiv.1912.02629openalex-snapshot

A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection

inferredcites →https://doi.org/10.48550/arxiv.2006.00618openalex-snapshot

Applying support vector data description for fraud detection

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4980350openalex-extracted

Enhancing Performance of Financial Fraud Detection Through Machine Learning Model

inferred← citeshttps://doi.org/10.1007/978-981-96-0139-4_1openalex-snapshot

Benchmarking One Class Classification in Banking, Insurance, and Cyber Security

inferred← citeshttps://doi.org/10.1109/bigdata55660.2022.10020494openalex-snapshot

DBNex: Deep Belief Network and Explainable AI based Financial Fraud Detection

inferred← citeshttps://doi.org/10.1109/icait65209.2024.10754927openalex-snapshot

A Predictive Analytics Framework for Fraud Detection Using Efficient Resampling Based on Hybrid Ensemble Machine Learning

inferred← citeshttps://doi.org/10.1109/snpd65828.2025.11488171openalex-snapshot

Support Vector Machines: An Inclusive Survey in Financial Fraud Detection

inferred← citeshttps://doi.org/10.1109/tifs.2024.3428412openalex-snapshot

ASIA: A Federated Boosting Tree Model Against Sequence Inference Attacks in Financial Networks

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