基于kNN算法的流量智能化模型在医院信息系统安全运维管理中的应用  

Application of Traffic Intelligent Model Based on kNN Algorithm in the Safe Operation and Maintenance Management of Hospital Information System

作　　者：王泽川 马存宁 刘玉泉[1] 袁雪 胡欣 王杰[1] 曹新志 WANG Zechuan;MA Cunning;LIU Yuquan;YUAN Xue;HU Xin;WANG Jie;CAO Xinzhi(Information Center,Jiangsu Province Hospital on Integration of Chinese and Western Medicine,Nanjing Jiangsu 210028,China)

机构地区：[1]江苏省中西医结合医院信息中心,江苏南京210028

出　　处：《中国医疗设备》2021年第6期132-135,171,共5页China Medical Devices

摘　　要：目的本文旨在保障医院信息系统的稳定性,更好地监测信息系统的运行状态、定位波动产生的原因,给医院整体网络的运维和管理带来便利。方法通过利用k最邻近算法,构建一种自学习智能化模型,可对信息系统响应时延和安全事件进行监测和分析,并生成预警和告警事件。结果在对信息系统网络设备、安全设备做配置预防后,出现问题时快速根据历史模型判定问题,无需大量人为分析,准确发现和处置事件。结论经过实际环境测试,本模型可有效检出分布式拒绝服务攻击、网络环路、并发数据限制,为今后医院信息系统稳定性监测提供了理论和实践参考。Objective To ensure the stability of the hospital information system,better monitor the operational status of the information system,locate the causes of the fluctuation,and bring convenience to the operation and management of the overall hospital network.Methods With the k-nearest neighbor algorithm,a self-learning intelligent model was constructed,which could monitor and analyze the response delay and security events of the information system,and generate an early warning and alarm events.Results The network equipment and security equipment of the information system were configured for prevention,and after that the problem could be quickly determined according to the antique model without extensive manual analysis,and the event could be accurately found and handled.Conclusion After testing in a practical environment,this model can effectively detect distributed denial of service attacks,network loops,and concurrent data limitation,so that to provide a theoretical and practical reference for future hospital information system stability monitoring.

关 键 词：信息系统 稳定性监测 KNN算法 自学习 

分 类 号：R197.32[医药卫生—卫生事业管理]