Quarterly journal published in SPbPU
and edited by prof. Peter Zegzhda
Peter the Great St. Petersburg Polytechnic University
Institute of computer sciences and technologies
information security of computer systems
Information Security Problems. Computer Systems
Published since 1999.
ISSN 2071-8217
PREDICTING NETWORK ATTACKS ON IOT SYSTEMS USING REGRESSION ANALYSIS

Lavrova D.S., Strukova N.E
Peter the Great St.Petersburg Polytechnic University
Russia, St.Petersburg

Annotation: The aim of the study is to improve the accuracy of IoT network attack detection by applying feature selection methods based on regression models. An analysis of the security problems of IoT systems is presented. The architecture of an intrusion detection system using the considered methods is developed. A software layout that implements the proposed architecture is developed and its effectiveness is evaluated.
Keywords: Internet of Things, intrusion detection system, network attack detection, prediction, significance assessment, feature selection.
Pages 39-50