Empirical research of the distribution function of synchronization time of neural networks in the key exchange protocol

Authors

  • Олена Романівна Малік National Technical University of Ukraine "Kyiv Polytechnic Institute, 37, Prospect Peremohy, Kyiv -56, Ukraine, 03056, Ukraine https://orcid.org/0000-0002-9687-1294

DOI:

https://doi.org/10.15587/2312-8372.2014.26288

Keywords:

neural networks, mutual learning, key exchange protocol

Abstract

Neurocryptography is relatively new and little-studied area. Existing results show the prospects of this direction, but practical application requires a fairly complete analysis of existing protocols and systems. Analysis of the features of the key exchange protocol, which is built using the mutual learning of special-type neural networks - tree parity machines was conducted in the paper. Known existing protocol attack strategies were considered. A special part of the protocol is determining the synchronization moment of the neural networks of subscribers. The studies have revealed that the average number of the protocol iterations, required for synchronization significantly differs from the maximum value. To achieve the goal, the work of the protocol with a fairly large number of different neural networks was simulated. The synchronization time feature, found in the work shows the vulnerability of the studied protocol since it allows an intruder to carry out one of the known protocol attack strategies.

Author Biography

Олена Романівна Малік, National Technical University of Ukraine "Kyiv Polytechnic Institute, 37, Prospect Peremohy, Kyiv -56, Ukraine, 03056

Department of mathematical methods of information security

Physico-Technical Institute

References

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Published

2014-07-24

How to Cite

Малік, О. Р. (2014). Empirical research of the distribution function of synchronization time of neural networks in the key exchange protocol. Technology Audit and Production Reserves, 4(1(18), 26–31. https://doi.org/10.15587/2312-8372.2014.26288

Issue

Vol. 4 No. 1(18) (2014): Technology audit

Section

Technology audit

License

Copyright (c) 2016 Олена Романівна Малік

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