聚类分析
计算机科学
数据挖掘
模糊逻辑
星团(航天器)
比例(比率)
模糊聚类
人工智能
地理
计算机网络
地图学
作者
Sharmila Subudhi,Suvasini Panigrahi
出处
期刊:Advances in intelligent systems and computing
日期:2017-01-01
卷期号:: 633-641
被引量:8
标识
DOI:10.1007/978-981-10-3874-7_60
摘要
This paper presents a novel approach for detecting fraudulent activities in mobile telecommunication networks by using a possibilistic fuzzy c-means clustering. Initially, the optimal values of the clustering parameters are estimated experimentally. The behavioral profile modelling of subscribers is then done by applying the clustering algorithm on two relevant call features selected from the subscriber’s historical call records. Any symptoms of intrusive activities are detected by comparing the most recent calling activity with their normal profile. A new calling instance is identified as malicious when its distance measured from the profile cluster centers exceeds a preset threshold. The effectiveness of our system is justified by carrying out large-scale experiments on a real-world dataset.
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