摘要
为应对电信诈骗的隐蔽性和难防性,提出了一种基于运营商OSS域数据的反诈模型,目的是满足大众日益增长的电信诈骗防控需求。利用OSS域用户行为数据,结合电信网络诈骗行为特征,采用机器学习方法构建了一套网络诈骗洞察与防范软件,可实现对诈骗行为的有效识别。采用国内知名互联网信息安全平台数据进行交叉验证,结果表明该模型能够有效鉴别恶意用户,具有较高准确率,具有较强可操作性,为电信诈骗防范提供了有力支撑。
In order to deal with the concealment and difficulty of communication fraud,this study proposes an anti-fraud model based on operator OSS domain data to meet the growing demand for communication fraud prevention and control.This model uses OSS domain user behavior data,combined with the characteristics of network telecom fraud behavior,using machine learning methods to build a set of network fraud insight and prevention software,to achieve effective recognition of fraud.The research uses the data of domestic well-known Internet information security platform for cross-validation.The results show that the method can effectively identify malicious users and has high accuracy and strong operability,providing strong support for communication fraud prevention.
作者
唐燕
TANG Yan(Hunan Branch of China Telecom Co.,Ltd.,Changsha,Hunan,China 410011)
出处
《湖南邮电职业技术学院学报》
2023年第2期31-34,共4页
Journal of Hunan Post and Telecommunication College
关键词
OSS
运营支撑系统
反诈模型
机器学习
OSS
operation support system
anti-fraud model
machine learning
作者简介
唐燕(1976-),女,湖南长沙人,中国电信股份有限公司湖南分公司工程师,学士,研究方向:互联网信息技术。
