摘要
随着“互联网+”概念的普及,互联网业务平台快速发展,为用户提供了大量优质的产品,同时也提高了用户消费体验和服务品质。平台吸引了大量的用户并得到了用户的好评,但同时也有一些恶意用户高频地刷订单谋取利益,造成了平台自身与合作方的损失。为保障自身与合作伙伴的切身利益,业务平台迫切需要建立一个可以精准识别、实时判断高风险用户以及稳定可靠的风控体系,保证平台的安全运行。文章针对真实的环境,打造了一套基于规则引擎和机器学习模型的实时业务风控系统,从而实现业务平台对用户的精准识别,有效地支撑全网对抗黑产,挖掘和识别刷单、薅羊毛用户。
With the popularization of the concept of"Internet plus",the business platform has developed rapidly,providing users with a large number of high-quality equity products,and improving user experience and service quality.The platform has attracted a large number of users and has been highly praised by users.However,at the same time,some malicious users frequently brush orders for benefits,resulting in losses to the platform itself and partners.In order to protect the vital benefit of itself and partners,the business platform urgently needs to establish a stable and reliable risk control system that can accurately identify and judge high-risk users in real time,so as to ensure the safe operation of the platform.Based on the real project environment,this paper creates a risk control system based on rule engine and machine learning model in the business platform,so as to realize the accurate identification of users,effectively support the whole network to fight against black production,and mine and identify bill brushing and wool picking users.
作者
黄健文
丁奕
苏丽裕
闫宇
匡磊怀
HUANG Jianwen;DING Yi;SU Liyu;YAN Yu;KUANG Leihuai(China Mobile Internet Co.,Ltd.,Guangzhou 510000,China)
出处
《数字通信世界》
2022年第5期20-22,共3页
Digital Communication World