[1]倪 震,李千目,郭雅娟.面向电力大数据日志分析平台的异常监测集成预测算法[J].南京理工大学学报(自然科学版),2017,41(05):634.[doi:10.14177/j.cnki.32-1397n.2017.41.05.016]
 Ni Zhen,Li Qianmu,Guo Yajuan.Ensemble forecasting algorithm for anomaly detection onelectric-power big data log analysis platform[J].Journal of Nanjing University of Science and Technology,2017,41(05):634.[doi:10.14177/j.cnki.32-1397n.2017.41.05.016]
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面向电力大数据日志分析平台的异常监测集成预测算法()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年05期
页码:
634
栏目:
出版日期:
2017-10-31

文章信息/Info

Title:
Ensemble forecasting algorithm for anomaly detection onelectric-power big data log analysis platform
文章编号:
1005-9830(2017)05-0634-12
作者:
倪 震12李千目1郭雅娟3
1.南京理工大学 计算机科学与工程学院,江苏 南京 210094; 2.南京晓庄学院 信息工程学院,江苏 南京 210017; 3.国网江苏省电力公司 电力科学研究院,江苏 南京 211100
Author(s):
Ni Zhen12Li Qianmu1Guo Yajuan3
1.School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China; 2.School of Information Engineering,Nanjing Xiaozhuang University,Nanjing 210017,China; 3.Electric Power Research Institute,Jiangsu Electric Power Company,Nanjing 211100,China
关键词:
日志分析 异常监测 大数据平台 集成预测算法
Keywords:
log analysis anomaly detection big data platform ensemble forecasting algorithm
分类号:
TP393.08
DOI:
10.14177/j.cnki.32-1397n.2017.41.05.016
摘要:
随着电力企业网络技术的发展,传统和新生的日志处理系统已不能满足大数据状态下的日志分析要求,为了实现系统日志异常分析的目标,该文提出一种基于时间序列的系统异常数量集成预测算法和面向该算法的评价体系。该算法对多种分类预测算法进行集成,对收集到的日志数据进行分类预测,进而实现了以综合最优的准确度预测系统的异常数量,评价体系很好地支持了该算法的工作,算法增强了日志分析平台的安全性。
Abstract:
In view of that the traditional or the new log processing system can not meet the requirements of the log analysis in the current situation of big data entirely with the development of power enterprise network technology,an algorithm for estimating the number of systems based on time series and the evaluation system are presented to realize the system for the algorithm.The algorithm integrates multiple classification prediction algorithms to classify the collected log data,and then realize the purpose of forecasting the number of anomaly systems with the best accuracy.The evaluation system also supports that the algorithm can increase the security of the log analysis platform.

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备注/Memo

备注/Memo:
收稿日期:2017-05-26 修回日期:2017-08-26

基金项目:国网公司科技项目; 江苏省重大研发计划产业前瞻项目(BE2017100); 赛尔下一代互联网创新项目(NGII20160122)
作者简介:倪震(1980-),男,博士生,讲师,主要研究方向:信息安全、数据挖掘,E-mail:nizhen0523@189.cn; 通讯作者:李千目(1979-),男,博士,教授,博士生导师,主要研究方向:大数据挖掘和数据处理,网络空间安全软件系统,E-mail:liqianmu@126.com。
引文格式:倪震,李千目,郭雅娟.面向电力大数据日志分析平台的异常监测集成预测算法[J].南京理工大学学报,2017,41(5):634-645.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-09-30