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Fraud detection: A systematic literature review of graph-based anomaly detection approaches

机译:欺诈检测:基于图形的异常检测方法的系统文献综述

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摘要

Graph-based anomaly detection (GBAD) approaches are among the most popular techniques used to analyze connectivity patterns in communication networks and identify suspicious behaviors. Given the different GBAD approaches proposed for fraud detection, in this study, we develop a framework to synthesize the existing literature on the application of GBAD methods in fraud detection published between 2007 and 2018. This study aims to investigate the present trends and identify the key challenges that require significant research efforts to increase the credibility of the technique. Additionally, we provide some recommendations to deal with these challenges.
机译:基于图形的异常检测(GBAD)方法是用于分析通信网络中的连接模式的最流行的技术,并识别可疑行为。鉴于欺诈检测所提出的不同GBAD方法,在本研究中,我们制定了一个框架,综合了关于在2007年至2018年间发布发布的欺诈检测中的GBAD方法的现有文献。本研究旨在调查当前趋势并确定关键需要重大研究努力提高技术可信度的挑战。此外,我们还提供了一些建议来处理这些挑战。

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