PRELIMINARY ANALYSIS AND PREPARATION OF DATA FOR CYBERATTACK TRENDS PREDICTION
Abstract
The article is devoted to the topical issue of combating cyberattacks through the use of forecasting methods. This issue is a consequence of the development of automation in various spheres of society and essential commercial and state companies. Cyber attacks can target multiple infrastructure facilities, which can cause power outages, disable equipment, and steal sensitive data that compromise a country's national security. The current situation related to cyber-attacks was analyzed, and the trends in studying this problem by scientists from various scientific schools and countries were investigated. The research proposed a conceptual model for predicting trends in cyberattacks, which involves the implementation of the preliminary analysis and data preparation stage and the stage of developing a predictive model. Calculations were made based on panel data generated for 40 countries and 30 days. Three types of time trends of cyber-attacks were used as a database of empirical data: the flow of data from malicious programs, suspicious and unwanted mail traffic, and data from detected network attacks. The analysis of the basic statistics revealed the heterogeneity of the data due to the different levels of the countries' development taken for the calculations. The implemented decomposition of trends established the absence of a trend component in the series, the presence of a seasonal element and an additive relationship between the model's parts. An extended Dickey-Fuller test was performed, which confirmed the stationarity of the studied series. The Jarque-Bera test made it possible to reveal the inconsistency of the data with a normal distribution, resulting in the transformation of the variables "x" by logarithmization. The conducted data preparation made it possible to prepare the data for building predictive models of cyberattack trends. Combined regression and regressions with random and fixed effects were chosen as such models. In the future, it is planned to carry out appropriate calculations, build predictive models, assess their accuracy and adequacy, and make forecasts for short-term periods for various countries.
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