Large-scale automated forecasting for network safety and security monitoring

被引:1
|
作者
Naveiro, Roi [1 ]
Rodriguez, Simon [1 ]
Rios Insua, David [1 ]
机构
[1] CSIC, ICMAT, Inst Math Sci, Madrid 28049, Spain
关键词
Bayesian methods; dynamic models; forecasting; network monitoring; real-time predictive analytics;
D O I
10.1002/asmb.2436
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Large-scale real-time streaming data pose major challenges to forecasting, in particular, defying the presence of human experts to perform the required analysis. We present here a class of models and methods used to develop an automated, scalable, and versatile system for large-scale forecasting oriented toward network safety and security monitoring. Our system provides short- and long-term forecasts and uses them to detect issues, well in advance, that might take place in relation with multiple Internet-connected devices.
引用
收藏
页码:431 / 447
页数:17
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