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
ANOMALY DETECTION IN CYBER-PHYSICAL SYSTEMS USING GRAPH NEURAL NETWORKS

Ivanov M.I., Pavlenko E. Y.

Annotation: This paper presents a security study of networks with dynamic topology. As a solution to the problem of attack detection, an approach to attack detection in networks with dynamic topology based on adaptive neuro-fuzzy inference system was developed. A software layout of the system that implements the proposed approach has been developed and its effectiveness has been evaluated using various metrics. Experimental results confirmed the validity and effectiveness of the developed approach for attack detection in networks with dynamic topology.
Keywords: dynamic topology networks, attack detection, network security, machine learning, fuzzy logic, neural networks
Pages 21-40