Statistical monitoring of a web server for error rates: a bivariate time-series copula-based modeling approach

被引:4
|
作者
Ara, Anderson [1 ]
Louzada, Francisco [2 ]
Diniz, Carlos A. R. [3 ]
机构
[1] Univ Fed Bahia, Dept Stat, Salvador, BA, Brazil
[2] Univ Sao Paulo, Dept Appl Math & Stat, Sao Paulo, Brazil
[3] Univ Fed Sao Carlos, Dept Stat, Sao Carlos, SP, Brazil
关键词
ARMA; copula; bivariate time series; errors rate; monitoring;
D O I
10.1080/02664763.2016.1238041
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The monitoring of web servers through statistical frameworks is of utmost important in order to verify possible suspicious anomalies in network traffic or misuse actions that compromise integrity, confidentiality, and availability of information. In this paper, by considering the Plackett copula function, we propose a bivariate beta-autoregressive moving average time-series model for proportion data over time, which is the case for variables present in web server monitoring such as error rates. To illustrate the proposed methodology, we monitor a Brazilian web server's rate of connection synchronization and rejection errors in a web system, with error logging rate in the past 10min. In essence, the entire methodology may be generalized to any number of time-series of error rates.
引用
收藏
页码:2287 / 2300
页数:14
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