Parallel Outlier Detection in Dial-back Fraud Calls
- DOI
- 10.2991/iccia.2012.119How to use a DOI?
- Keywords
- Illegal activities,Outlier detection,Cluster Coefficient, MapReduce,Parallelization,
- Abstract
With the intensified competition among telecommunications industry, we focused much on the quality of service. Illegal activities, especially dial-back fraud calls, may cause annoyance and inconvenience which will reduce user experience. The detection of dial-back fraud calls is an urgent issue that needs to be addressed. The rapid development of information technology which gives rise to the accumulated huge data will pose a greater challenge. However, traditional detecting methods to identify illegal activities cannot get acceptable accuracy. On the other hand, those methods become very inefficient or even unavailable when processing massive data. In this paper, we introduce a distributed outlier detection approach to locate illegal acts of the illegal users who have the characteristics as outliers. For a higher hit rate, we combine outlier detection with cluster coefficient. Besides, the method exploits parallel computation based on MapReduce in order to obtain vast time savings and improve the processing capability of the algorithm on large data. Extensive experimental results demonstrate the efficiently performances of proposed algorithm according to the evaluation criterions of speedup and scale up.
- Copyright
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Bin Wu AU - Fandi Liao AU - Di Zhang PY - 2014/05 DA - 2014/05 TI - Parallel Outlier Detection in Dial-back Fraud Calls BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 494 EP - 497 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.119 DO - 10.2991/iccia.2012.119 ID - Wu2014/05 ER -