基于Hadoop的大数据平台风险监测系统研究

Research on Big Data Platform Risk Monitoring System Based on Hadoop

随着云计算大数据技术的发展,传统的安全监测技术无法满足不间断服务的应用需求。本文所设计系统基于一种检测模型,实现对大数据平台风险进行检测,系统模型可防止主机管理环境下的入侵检测保护系统分布式DDoS攻击。模型设计过程中使用主成分分析和线性判别分析元启发式算法,被称为是Ant Lion优化,通过神经网络实现特征选择,实现对云服务器分类和配置。系统测试结果显示该模型对基于云环境的大数据平台的安全风险预测有较好的性能。

With the development of cloud computing big data technology,traditional security monitoring technology cannot meet the application requirements of uninterrupted services.The system designed in this paper is based on a detection model to detect the risks of big data platforms.The system model can prevent the distributed DDoS attacks of the intrusion detection and protection system under the host management environment.The model design process uses principal component analysis and linear discriminant analysis meta-heuristic algorithm,which is called Ant Lion optimization,which implements feature selection through neural network and classifies and configures cloud servers.The system test results show that the model has good performance in the security risk prediction of the big data platform based on the cloud environment.