Abstract
Cyber security is an integral part of security system of any advanced country. Given the fact that the number of cyber attacks constantly increase with concurrent increase of their technological complexity, the paper proposes a new classifier structure to speed up detection of unauthorized interference while maintaining the established accuracy parameters. Method of reducing input data-flow dimensions is the basis for the designed structure of cyber attacks classifier. Unlike other well-known classifier principles, this one is based on a binary type classification of event patterns and two-stage scheme of network connection input data classification. The classifier is verified on the basis of real data and compared with advanced world standards. The results have confirmed the ability of the classifier to quickly detect and classify cyber attacks without loss of accuracy.
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Korobiichuk, I., Hryshchuk, R., Mamarev, V., Okhrimchuk, V., Kachniarz, M. (2018). Cyberattack Classificator Verification. In: Kościelny, J., Syfert, M., Sztyber, A. (eds) Advanced Solutions in Diagnostics and Fault Tolerant Control. DPS 2017. Advances in Intelligent Systems and Computing, vol 635. Springer, Cham. https://doi.org/10.1007/978-3-319-64474-5_34
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DOI: https://doi.org/10.1007/978-3-319-64474-5_34
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