System for Detection of Network Threats based on Classifiers

Autor:	Bilgin Demir, Zoran Gacovski, Vladimir Pivovarov, Lidija Goracinova
Jazyk:	angličtina
Rok vydání:	2015
Předmět:	ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS lcsh:T Intrusion detection Classification methods Network vulnerabilities lcsh:L lcsh:Technology lcsh:Education
Zdroj:	TEM Journal, Vol 3, Iss 2, Pp 120-126 (2015)
ISSN:	2217-8333 2217-8309
Popis:	In this paper we present a system that automatically detects and profiles threats on a real network. The realised Threat Detection System (TDS)is based on Snort software and it allows the security experts to evaluate the risk of vulnerability and to retrieve the actual number of threats that are active in the network.Algorithms are presented to determine three properties for each threat: skill, intensity of the attacks and whether the threat is a human or an autonomous computer program.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doajarticles::3b9d69f093555c573f4993d73fcc9761 Zobrazit plný text záznamu