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
AN APPROACH TO DETECTING BOTNET ATTACKS IN THE INTERNET OF THINGS NETWORKS

T. M. Tatarnikova, I. A. Sikarev, P. Yu. Bogdanov, T. V. Timochkina
Sankt-St. Petersburg State Electrotechnical University “LETI”
Sankt-St. Petersburg State University of Aerospace Instrumentation
Russian State Hydrometeorological University

Annotation: An approach to detecting network attacks based on deep learning methods — autoencoders is proposed. It is shown that training examples can be obtained when connecting IoT devices to the network, as long as the traffic does not carry malicious code. Statistical values and functions extracted from traffic are proposed, on which patterns of behavior of IoT devices are built.
Keywords: Internet of Things, Network Attack, Attack Detection System, Autoencoder, Principal Component Method, Unsupervised Learning.
Pages 108-117