A systematic review of literature on credit card cyber fraud detection using machine and deep learning

The increasing spread of cyberattacks and crimes makes cyber security a top priority in the banking industry. Credit card cyber fraud is a major security risk worldwide. Conventional anomaly detection and rule-based techniques are two of the most common utilized approaches for detecting cyber fraud,...

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Veröffentlicht in:PeerJ. Computer science Jg. 9; S. e1278
Hauptverfasser: Marazqah Btoush, Eyad Abdel Latif, Zhou, Xujuan, Gururajan, Raj, Chan, Ka Ching, Genrich, Rohan, Sankaran, Prema
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States PeerJ. Ltd 17.04.2023
PeerJ Inc
Schlagworte:
Algorithms and Analysis of Algorithms
Artificial Intelligence
Bank industry
Banks (Finance)
Credit and debit card industry
Credit card cyber fraud
Credit card fraud
Cyber security
Cyberterrorism
Data Mining and Machine Learning
Deep learning
Fraud investigation
Internet fraud
Machine learning
Phishing
Security and Privacy
Deep learning
Bank industry
Artificial intelligence
Credit card cyber fraud
Cyber security
Machine learning
ISSN:2376-5992, 2376-5992
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Zusammenfassung:The increasing spread of cyberattacks and crimes makes cyber security a top priority in the banking industry. Credit card cyber fraud is a major security risk worldwide. Conventional anomaly detection and rule-based techniques are two of the most common utilized approaches for detecting cyber fraud, however, they are the most time-consuming, resource-intensive, and inaccurate. Machine learning is one of the techniques gaining popularity and playing a significant role in this field. This study examines and synthesizes previous studies on the credit card cyber fraud detection. This review focuses specifically on exploring machine learning/deep learning approaches. In our review, we identified 181 research articles, published from 2019 to 2021. For the benefit of researchers, review of machine learning/deep learning techniques and their relevance in credit card cyber fraud detection is presented. Our review provides direction for choosing the most suitable techniques. This review also discusses the major problems, gaps, and limits in detecting cyber fraud in credit card and recommend research directions for the future. This comprehensive review enables researchers and banking industry to conduct innovation projects for cyber fraud detection.
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ISSN:2376-5992
2376-5992
DOI:10.7717/peerj-cs.1278