PFrauDetector: a parallelized graph mining approach for efficient fraudulent phone call detection
Paper
Paper/Presentation Title | PFrauDetector: a parallelized graph mining approach |
---|---|
Presentation Type | Paper |
Authors | Ying, Josh Jia-Ching (Author), Zhang, Ji (Author), Huang, Che-Wei (Author), Chen, Kuan-Ta (Author) and Tseng, Vincent S. (Author) |
Journal or Proceedings Title | Proceedings of the 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS 2016) |
ERA Conference ID | 43485 |
Number of Pages | 8 |
Year | 2016 |
Place of Publication | United States |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ICPADS.2016.0140 |
Web Address (URL) of Paper | http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7823855 |
Conference/Event | 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS 2016) |
International Conference on Parallel and Distributed Systems | |
Event Details | International Conference on Parallel and Distributed Systems ICPADS Rank B B B B B B |
Event Details | 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS 2016) Event Date 13 to end of 16 Dec 2016 Event Location Wuhan, China |
Abstract | In recent years, fraud is becoming more rampant internationally with the development of modern technology and global communication. Due to the rapid growth in the volume of call logs, the task of fraudulent phone call detection is confronted with Big Data issues in real-world implementations. While our previous work, FrauDetector, has addressed this problem and achieved some promising results, it can be further enhanced as it focuses on the fraud detection accuracy while the efficiency and scalability are not on the top priority. Meanwhile, other known |
Keywords | telecommunication fraud; trust value mining;fraudulent phone call detection; parallelized weighted HITSalgorithm |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Public Notes | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Byline Affiliations | Feng Chia University, Taiwan |
Faculty of Health, Engineering and Sciences | |
National Cheng Kung University, Taiwan | |
Academia Sinica, Taiwan | |
National Chiao Tung University, Taiwan | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3w4w/pfraudetector-a-parallelized-graph-mining-approach-for-efficient-fraudulent-phone-call-detection
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