A survey of anomaly detection techniques in financial domain
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- 作者：Mohiuddin Ahmeda ; Mohiuddin.Ahmed@student.adfa.edu.au" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Abdun Naser Mahmooda ; a.mahmood@adfa.edu.au" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Md. Rafiqul Islamb ; mislam@csu.edu.au" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Clustering ; Fraud detection ; Anomaly detection
- 刊名：Future Generation Computer Systems
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：55
- 期：Complete
- 页码：278-288
- 全文大小：839 K
文摘
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Recently, in the financial sector, there has been renewed interest in research on detection of fraudulent activities.
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This paper presents an in-depth survey of various clustering based anomaly detection techniques and compares them from different perspectives.
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In addition, we discuss the lack of real world data and how synthetic data has been used to validate current detection techniques.