STATISTICAL METHODS FOR PREDICTING PHISHING ATTACKS

Abstract

The article proposes a methodology for predicting so-called phishing attacks, which are a common form of cybercrime, the number of which is growing every year, and the level of their harmful impact on the information systems of critical infrastructure objects is also increasing. To analyze trends and predict phishing attacks, we used statistical data published in scientific works of domestic and foreign researchers, as well as published by online publications of leading consulting companies working in the field of information security and cybersecurity. Statistical methods based on the use of time series, as one of the popular approaches used to predict various technological and economic processes, were chosen as tools for researching and predicting phishing attacks. This made it possible to analyze the types and patterns of phishing attacks that attackers use to disrupt the operation of software of information and communication systems and automated systems. Based on time series analysis, a trend model was built for the number of detected phishing attacks for the period 2020–2023. A calculation was made of the predicted number of phishing attacks for 16 quarters of 2020–2023, as well as the estimated forecast of the occurrence of these attacks for four quarters of 2024. To improve the forecast, a coefficient taking into account the seasonality factor was calculated and a correlation and regression analysis of the impact of phishing attacks on the total number of attacks detected during 2020–2023 was performed. Calculations have been performed, indicating that the discrepancies in the predicted values are not significant; the results presented allow us to select the optimal strategy for identifying, predicting and eliminating computer attacks related to phishing. Based on the time series model and the calculations obtained, it was concluded that statistical forecasting methods make it possible to build a forecast of phishing attacks, provide in the future the opportunity to develop and formulate methods for countering these attacks, and plan measures to increase the level of security of information resources.