E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review
Author:
Affiliation:
1. NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide,Lisboa,Portugal,1070-312
Publisher
Tsinghua University Press
Link
http://xplorestaging.ieee.org/ielx7/8254253/10506765/10506811.pdf?arnumber=10506811
Reference175 articles.
1. Increasing Cybercrime Since the Pandemic: Concerns for Psychiatry
2. Detecting problematic transactions in a consumer-to-consumer e-commerce network
3. The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature
4. Online payment fraud: Market forecasts, emerging threats & segment analysis 2022–2027,2024
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1. Emerging Technologies in E-Commerce Security;Advances in Electronic Commerce;2024-09-27
2. Multi-Relational Graph Representation Learning for Financial Statement Fraud Detection;Big Data Mining and Analytics;2024-09
3. Machine Learning Algorithms for E-Commerce Security;Advances in Web Technologies and Engineering;2024-08-30
4. Cybersecurity Strategies for E-Commerce;Advances in Web Technologies and Engineering;2024-08-30
5. Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data;Journal of Sensor and Actuator Networks;2024-08-03
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