Quarterly journal published in SPbPU
and edited by prof. Dmitry 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
SYNTHETIC DATA GENERATION FOR HONEYPOT SYSTEMS USING DEEP LEARNING METHODS

V. D. Danilov, T. D. Ovasapyan, D. V. Ivanov, A. S. Konoplev
Peter the Great St. Petersburg Polytechnic University

Annotation: This article presents research aimed at analyzing methods for generating synthetic data to populate honeypot systems. To select the generated data types, the relevant target objects in the context of honeypot-systems are identified. Existing generation methods are investigated. Methods for evaluating the quality of generated data in the context of honeypot systems are also analyzed. As a result, a layout of an automated system for generating synthetic data for honeypot-systems is developed and its performance is evaluated.
Keywords: honeypot system, deep learning methods, synthetic data generation, machine learning, inference attacks
Pages 96-109