Exploring new scenarios of adversarial attacks on pattern recognition neural networks in the context of finding new defense methods

DOI: 10.21293/1818-0442-2025-28-1-114-118

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Abstract: Neural networks (NNs) are an effective tool for solving hardto-formalize problems, which has made them indispensable tools for solving them. However, information defense techniques in this area still lack sufficient protection, making them vulnerable to cybercriminals. This paper investigates adversarial attacks on neural networks, their characteristics, and proposes a new technique for detecting adversarial attacks.

Keywords: neural networks, machine learning, information security, adversarial attacks

For citation:
Dyudyun G. D., Lapina M. A., Babenko M. G. Exploring new scenarios of adversarial attacks on pattern recognition neural networks in the context of finding new defense methods. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2025, vol. 28, no. 1, pp. 114–118. DOI: 10.21293/1818-0442-2025-28-1-114-118

Authors and copyright holders:

  • Dyudyun G. D. , North Caucasus Federal University (Stavropol, Russia)
  • Lapina M. A. , North Caucasus Federal University (Stavropol, Russia)
  • Babenko M. G. , North Caucasus Federal University (Stavropol, Russia)

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