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Multivariate Time Series Modeling for Information Security Data  

Choi, Han Young (Department of Applied Statistics, University of Suwon)
Jeong, Hyeong Chul (Department of Applied Statistics, University of Suwon)
Publication Information
Journal of the Korean Data Analysis Society / v.17, no.3B, 2015 , pp. 1309-1318 More about this Journal
Abstract
In this paper, we considered the multivariate time series analysis using the state space model related to information securities data which were the numbers of Korean domain registration, the numbers of receipt for hacking incidents, reporting numbers of malware, the numbers of detection in MC-Finder system, and influx numbers of malware into Honey net. The similarity index was used to explore the relevance between the variables. The VARMA(2,1) was fitted for the variables of domain, malware and hacking, and VARMA(1,1) was fitted for the variables of malware, MC-Finder and Honey net. There was a AR term mainly involved in VARMA(2,1) and a MA term involved in VARMA(1,1). Especially, malware was affected by the 1-step previous values of MC-Finder. For the comparison of forecasting capability, we used the RMSE of exponential smoothing model and autoregressive integrated moving average model. Except Honey-net series, multivariate model was provided better forecasting performance than the other univariate time series models.
Keywords
Information security; Multivariate time series; Similarity index; Space state model; Univariate time series model;
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Times Cited By KSCI : 3  (Citation Analysis)
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