...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Vietnam Journal of Computer Science >A hybrid mobile call fraud detection model using optimized fuzzy C-means clustering and group method of data handling-based network
【24h】

A hybrid mobile call fraud detection model using optimized fuzzy C-means clustering and group method of data handling-based network

机译：基于优化模糊C-均值聚类的混合移动电话欺诈检测模型及基于数据处理的网络分组方法

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A novel two-stage fraud detection system in mobile telecom networks has been presented in this paper that identifies the malicious calls among the normal ones in two stages. Initially, a genetic algorithm-based optimized fuzzy c-means clustering is applied to the user’s historical call records for constructing the calling profile. Thereafter, the identification of the fraudulent calls occurs in two stages. In the first stage, each incoming call is passed to the clustering module that identifies the call as genuine, malicious or suspicious. This is done by comparing the distance value of the new calling instance from the profile cluster centers against two predefined threshold values. The calls detected as genuine or malicious are not further processed. However, the call records that are found to be suspicious are additionally scrutinized in the second stage by a previously trained group method of data handling model for final decision making. The legitimate and forged labeled call records generated out of the clustering module are utilized for training the supervised classifier. Experimentation is done on a real-world call dataset to exhibit the effectiveness of the proposed model. A comparative analysis of the current approach with one of our earlier propositions and another recent fraud detection system clearly illustrates the efficacy of the developed model.
机译：本文提出了一种新颖的移动电信网络两阶段欺诈检测系统，该系统可以在两个阶段识别正常呼叫中的恶意呼叫。最初，将基于遗传算法的优化模糊c均值聚类应用于用户的历史通话记录，以构建通话档案。此后，欺诈性呼叫的识别分两个阶段进行。在第一阶段，每个传入呼叫都被传递到群集模块，该模块将呼叫标识为真实，恶意或可疑。这是通过将新的呼叫实例距配置文件群集中心的距离值与两个预定义的阈值进行比较来完成的。被检测为真实或恶意的呼叫不会进一步处理。但是，在第二阶段，通过先前训练有素的数据处理模型分组方法对发现为可疑的呼叫记录进行额外检查，以进行最终决策。从聚类模块生成的合法和伪造的带标签的呼叫记录用于训练监督分类器。实验在真实世界的呼叫数据集上进行，以展示所提出模型的有效性。对当前方法与我们较早的命题之一和另一个最新的欺诈检测系统进行的比较分析清楚地说明了开发模型的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号