基于遗传算法优化LightGBM算法的医院微服务平台安全运维管理系统的流量智能化检测-《中国医学物理学杂志》

文章信息/Info

Title:: Intelligent flow detection in hospital microservices platform security operation and maintenance management system based on genetic algorithm optimized LightGBM algorithm

Author(s):: ZHUO Yichao; HAO Haibin; Department of Medical Information, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China

Keywords:: Keywords: microservices platform operation and maintenance management system genetic algorithm LightGBM

摘要:: 为提升医院微服务平台下运维管理系统的数据检测效率，提出一种新的数据检测算法。该算法以平台数据的多元特征为基础，构建运维管理系统的整体框架。通过结合遗传算法的参数寻优能力和LightGBM算法的快速检测能力，实现对运维管理系统的流量数据的有效检测。为了验证模型的有效性，增加了对照实验。实验结果表明本方法在流量智能化检测中表现最优，其准确率（0.981 0）、查全率（0.68）以及F1值（0.77）均优于传统方法。

Abstract:: A novel data detection algorithm is proposed to improve the data detection efficiency of the operation and maintenance management system for the hospital microservices platform. Based on the multiple characteristics of the platform data, the algorithm constructs the overall framework of the operation and maintenance management system. By combining the parameter optimization ability of genetic algorithm and the rapid detection ability of LightGBM algorithm, the effective detection of the flow data in the operation and maintenance management system is realized. The effectiveness of the model is verified through a control test, and the results show that the proposed method performs the best in intelligent flow detection, achieving accuracy of 0.981 0, recall rate of 0.68 and F1 value of 0.77 which are all higher than those of the traditional methods.