RT Journal Article
T1 Countering Cybercrime Risks in Financial Institutions: Forecasting Information Trends
A1 Kuzior, Aleksandra
A1 Brozek, Paulina
A1 Kuzmendo, Olha
A1 Yarovenko, Hanna
A1 Vasilyeva, Tetyana
AB This article aims to forecast the information trends related to the most popular cyberattacks, seen as the cyber-crimes’ consequences reflecting on the Internet. The study database was formed based on online users’ search engine requests regarding the terms “Cyberattacks on the computer systems of a financial institution”, “Cyberattacks on the network infrastructure of a financial institution”, and “Cyberattacks on the cloud infra-structure of a financial institution”, obtained with Google Trends for the period from 16 April 2017 to 4 October 2022. The authors examined the data using the Z-score, the QS test, and the method of differences of average levels. The data were found to be non-stationary with outliers and a seasonal component, so exponential smoothing was applied to reduce fluctuations and clarify the trends. As a result, the authors built additive and multiplicative cyclical and trend-cyclical models with linear, exponential, and damped trends. According to the models’ quality evaluation, the best results were shown by the trend-cyclic additive models with an exponential trend for predicting cyberattacks on computer systems and the cloud infrastructure and a trend-cyclic additive model with a damped tendency for predicting cyberattacks on the network infrastructure. The obtained results indicate that the U.S. can expect cybercrimes in the country’s financial system in the short and medium term and develop appropriate countermeasures of a financial institution to reduce potential financial losses.
PB MDPI
SN 1911-8066
YR 2022
FD 2022-12-16
LK https://hdl.handle.net/10016/38681
UL https://hdl.handle.net/10016/38681
LA eng
NO This research was funded by the grant from the Ministry of Education and Science of Ukraine (No. s/r 0121U109559, No. s/r 0121U100467, No. s/r 0121U109553, No. s/r 0120U102001).The research received funding under the research subsidy of the Faculty of Organization and Management of the Silesian University of Technology for the year 2022 (13/990/BK_22/0170).
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RD 30 jun. 2024