Statistical monitoring of a web server for error rates: a bivariate time-series copula-based modeling approach. Issue 13 (3rd October 2017)

• Record Type: Journal Article
• Authors: Ara, Anderson; Louzada, Francisco; Diniz, Carlos A. R.
• Is Part Of: Journal of applied statistics. Volume 44:Issue 13(2017)
• Page Start: 2287
• Page End: 2300
• Publication Date: 2017-10-03
• Subjects: βARMA -- copula -- bivariate time series -- errors rate -- monitoring; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2016.1238041
• Languages: English
• ISSNs: 0266-4763

Abstract

ABSTRACT: 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 10 min. In essence, the entire methodology may be generalized to any number of time-series of error rates.