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September 18, 2025Sensors2 citationsOpen Access

A Study on IoT Device Authentication Using Artificial Intelligence

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SKShahram Miri KelanikiNKNikos Komninos

Key Points

  • Artificial intelligence improves authentication accuracy and efficiency, enhancing IoT security.
  • Machine learning techniques offer advantages over traditional methods for verifying legitimate devices.
  • The research explores AI algorithms including deep learning and reinforcement learning for authentication.
  • Recommendations highlight future challenges and opportunities in AI authentication mechanisms.

Abstract

Designing reliable authentication mechanisms for IoT devices is increasingly necessary to protect citizens’ private information and data. One of the most significant issues in today’s digital age is authentication. As IoT device technology advances and data grow rapidly, machine learning techniques improve the accuracy and efficiency of authentication and offer advantages over traditional methods, making them valuable in both academia and industry. Device authentication aims to verify legitimate computing devices and identify impostors based on their behavioral data. This paper explores research that applies artificial intelligence algorithms to enhance device authentication mechanisms. We discuss AI authentication models, including deep learning algorithms, convolutional neural networks, and reinforcement learning. We also highlight research challenges and provide recommendations for future studies to support innovation in this field.

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Cite This Study

Kelaniki et al. (2025) studied this question.

synapsesocial.com/papers/68d461c231b076d99fa60e62https://doi.org/10.3390/s25185809
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