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Technical gazette, Vol. 29 No. 6, 2022.

Original scientific paper

https://doi.org/10.17559/TV-20210325173601

Application of PSVR-DNS Algorithm for Attacker Detection and Isolation

Denis Pejić orcid id orcid.org/0000-0001-5742-7775 ; Faculty of Electrical Engineering, Computer Science and Information Technology, Ul. Kneza Trpimira 2b, 31000, Osijek, Croatia
Višnja Križanović ; Faculty of Electrical Engineering, Computer Science and Information Technology, Ul. Kneza Trpimira 2b, 31000, Osijek, Croatia
Drago Žagar ; Faculty of Electrical Engineering, Computer Science and Information Technology, Ul. Kneza Trpimira 2b, 31000, Osijek, Croatia

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Abstract

The DNS (Domain Name System) is used to map and convert human-friendly domain names to the numeric IP (Internet Protocol) addresses. As with the operation of any communication system, there are some security risks associated with the operation of DNS. Actions targeting the availability or stability of a network's DNS service are considered DNS attack. For example, a high volume of traffic and a large number of requests coming to DNS servers are part of a type of DoS (Denial of Service) attack that uses DNS for amplification. Although most DNS servers are open source, some commercial protective DNS services are available for network traffic control, filtering and automatic blocking of requests to undesirable, dangerous or malicious internet domains, but the price of such services is high. In this paper, a new PSVR-DNS (Probability Support Vector Regression-Domain Name System) algorithm is proposed for the purpose of detecting and isolating attackers who pose a threat to an uninterrupted work of the DNS servers. The main focus is on the prevention of the DNS cache poisoning. The collected results showed that the proposed PSVR-DNS algorithm achieves better performance related to faster detection and isolation of attacks compared to some existing algorithms.

Keywords

Bayesian probability; DoS attack; PSVR-DNS algorithm; SDN

Hrčak ID:

284891

URI

https://hrcak.srce.hr/284891

Publication date:

29.10.2022.

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