Analysis and Collection Data from IP Network

Martin Hasin, Martin Chovanec, Jakub Palša, Martin Havrilla

Analysis and Collection Data from IP Network

Číslo: 3/2022
Periodikum: Acta Electrotechnica et Informatica
DOI: 10.2478/aei-2022-0013

Klíčová slova: Cybersecurity, nfstream, database, ndpi, anomaly detection, machine learning

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Přečíst po přihlášení

Anotace: The rapid deployment of technologies that can share data brings, in addition to the positive aspects, also technologies that anattacker can use to misuse personal data. Vulnerabilities in the network can be divided according to the type of attack into horizontalattacks from the perspective of the attacker and vertical attacks from the perspective of the victim. An important goal of organizations isto successfully defend against such an attack. The search for attacks on the network infrastructure can be ensured by implementing ma-chine learning that can capture the current attack. This work describes methods of searching for attacks using graphical representationof data and also using machine learning of the high count type at different sizes of the investigated segments.