REVIEW OF MODELS FOR DETECTING A HIDDEN RADIO LINK FROM UNAUTHORIZED ACCESS TO THE INFORMATION OF THE PROTECTED OBJECT

A. I. Proskurin; Nadezhda Yudina

doi:doi:10.58168/PPSPM2025_142-147

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REVIEW OF MODELS FOR DETECTING A HIDDEN RADIO LINK FROM UNAUTHORIZED ACCESS TO THE INFORMATION OF THE PROTECTED OBJECT

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REVIEW OF MODELS FOR DETECTING A HIDDEN RADIO LINK FROM UNAUTHORIZED ACCESS TO THE INFORMATION OF THE PROTECTED OBJECT

Section: SECTION 1. SYSTEMS ANALYSIS, MANAGEMENT, INFORMATION PROCESSING

Proceedings: PROBLEMS AND PROSPECTS IN SYSTEMS AND PROCESS MODELING : MATERIALS OF THE ALL-RUSSIAN SCIENTIFIC AND PRACTICAL CONFERENCE, VORONEZH, OCTOBER 14, 2025

UDC 004.056

A. I. Proskurin ¹

Nadezhda Yudina ²

Author and publication information

Authors:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov

2. Voronezh State University of Forestry and Technologies named after G.F. Morozov (Departtment of Computer Science and Information Systems, assistant professor)
Voronezh, Voronezh, Russian Federation

Type:

Сonference article

DOI:

https://doi.org/10.58168/PPSPM2025_142-147

Pages:

from 142 to 147

Published:

30.12.2025

Subject area:

UDC 004.056

Language:

Russian

Keywords:

Signal, bandpass filter, signal-to-noise, Bayesian classifier, feature vector, optimal solution

Abstract and keywords

Abstract:
The paper discusses mathematical descriptions of models for detecting a hidden radio link. The problem of detecting a hidden radio link can be formulated as the problem of testing statistical hypotheses. Statistical decision theory defines the mathematical core of the hidden radio link detection model. The choice of a specific mathematical model depends on the amount of a priori information about the signal and the nature of the interference. Machine learning methods are the most flexible and powerful tool for working under uncertainty.

Keywords:
Signal, bandpass filter, signal-to-noise, Bayesian classifier, feature vector, optimal solution

References

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