基于通信网络的大数据防诈模型设计和研究

Design and research of big data fraud prevention model based on communication networks

近年来,电信网络诈骗犯罪形势十分严峻,已成为发案最多、上升最快、涉及面最广、人民群众反映最强烈的犯罪类型。基于电信通信网络,通过对公安、工信部通报诈骗号码的大数据挖掘分析,提取相似特征,利用机器学习、大数据、神经网络、遗传算法等开发大数据防诈模型,从数据采集、中间处理、模型生成、用户匹配、用户停机等全流程,及时关停疑似诈骗分子的号码,避免更多人蒙受诈骗,遭受损失。

In recent years,the situation of telecommunications network fraud has been very severe,becoming the type of crime with the most cases,the fastest increase,the widest coverage,and the strongest public feedback.This article is based on telecommuni-cations networks.Through big data mining and analysis of fraud numbers reported by the Ministry of Public Security and Industry and Information Technology,similar features are extracted.Machine learning,big data,neural networks,genetic algorithms,and other meth-ods are used to develop big data fraud prevention models.From data collection,intermediate processing,model generation,user match-ing,and user shutdown,the numbers of suspected fraudsters are promptly shut down to avoid more people suffering losses from fraud.