Cited By
View all- Ding RYang XWang B(2023)Themis: Detecting Anomalies from Disguised Normal Financial Activities2023 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM58522.2023.00016(71-80)Online publication date: 1-Dec-2023
POSTER: Actively Detecting Implicit Fraudulent Transactions
Authors: 
Shaosheng Cao, XinXing Yang, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi, Kai XiaoAuthors Info & Claims
Shaosheng Cao, XinXing Yang, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi, Kai XiaoAuthors Info & ClaimsPages 2475 - 2477
Abstract
In this work, we propose to actively detect implicit fraudulent transactions. A novel machine learning method is introduced to distinguish anomalous electronic transactions based on the historical records. The transferor will be alerted during the on-going payment when the fraud probability is recognized as large enough. Compared with elaborative rule-based approaches, our model is much more effective in fraud detection.
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Index Terms
- POSTER: Actively Detecting Implicit Fraudulent Transactions
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Information & Contributors
Information
Published In
October 2017
2682 pages
ISBN:9781450349468
DOI:10.1145/3133956
- General Chair:
- Bhavani Thuraisingham,
- Program Chairs:
- David Evans,
- Tal Malkin,
- Dongyan Xu
Copyright © 2017 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Published: 30 October 2017
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CCS '17
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CCS '17: 2017 ACM SIGSAC Conference on Computer and Communications Security
October 30 - November 3, 2017
Texas, Dallas, USA
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CCS '17 Paper Acceptance Rate 151 of 836 submissions, 18%;
Overall Acceptance Rate 1,261 of 6,999 submissions, 18%
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View all- Ding RYang XWang B(2023)Themis: Detecting Anomalies from Disguised Normal Financial Activities2023 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM58522.2023.00016(71-80)Online publication date: 1-Dec-2023
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