Work

Intrusion Detection based on an Intelligent Security System using Machine Learning Methods

Year: 2024

Type: conference-paper

Abstract: Authors have analyzed the basic concepts of cybersecurity, and cybersecurity technologies, studied the peculiarities of artificial intelligence application in cybersecurity, analyzed applied machine learning methods, and presented the results of experimental studies of the application of machine learning methods in cybersecurity. Intrusion detection based on an intelligent security system using machine learning methods, which is designed to detect the latest malicious URLs and is extended for distributed denial of service (DDoS) attacks, has been studied. Experimental studies and performance evaluations of the investigated SIS-ID system have been carried out.

Source: Workshop on Cybersecurity Providing in Information and Telecommunication Systems (CPITS)

DOI: 10.55056/ceur-ws.org/vol-3654/paper14.pdf

Authors: Svitlana Popereshnyak, Anastasiya Vecherkovskaya, Viktoriia Zhebka

Institutions: National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Taras Shevchenko National University of Kyiv, State University of Information and Communication Technologies

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: bronze

OpenAlex ID: W7166353050