计算机工程与应用 ›› 2023, Vol. 59 ›› Issue (21): 1-25.DOI: 10.3778/j.issn.1002-8331.2302-0129
蒋洪迅,江俊毅,梁循
出版日期:
2023-11-01
发布日期:
2023-11-01
JIANG Hongxun, JIANG Junyi, LIANG Xun
Online:
2023-11-01
Published:
2023-11-01
摘要: 机器学习在信用卡交易检测中有其特殊性,面对的环境更为复杂。由于有人的智力介入,战胜信用卡交易欺诈,其挑战性比人脸识别、无人驾驶等工程问题的难度更高,照搬工程学科的机器学习方法往往会失败。综述了2000年以来基于机器学习的信用卡欺诈检测研究历程,辨析了该领域的研究范畴、应用场景、技术流派等相关概念及其联系;解构了机器学习欺诈识别的一般性研究架构,从特征工程、模型算法、评价指标三个环节归纳总结了领域内研究的最新进展;从数据集是否具备标签角度,着重列举了面向欺诈识别的有监督的、无监督和半监督三类主流机器学习模型,讨论了这些模型的出发点、核心思想、求解方法以及优缺点;还分析了强化学习模型模拟欺诈者与机构之间的动态博弈过程;探讨了机器学习面临的海量数据、样本偏斜和概念漂移三大难点问题,并汇集整理了缓解这些问题的最新进展;总结了面向欺诈检测的机器学习研究目前存在的局限、争议和挑战,并为未来的研究方向提供趋势分析与建议。
蒋洪迅, 江俊毅, 梁循. 基于机器学习的信用卡交易欺诈检测研究综述[J]. 计算机工程与应用, 2023, 59(21): 1-25.
JIANG Hongxun, JIANG Junyi, LIANG Xun. Survey on Credit Card Transaction Fraud Detection Based on Machine Learning[J]. Computer Engineering and Applications, 2023, 59(21): 1-25.
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