A Study on IoT Device Authentication Using Artificial Intelligence

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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Publication Details

Journal
Sensors
Published
2025-09-17
DOI
https://doi.org/10.3390/s25185809
Citations
1
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
1.49
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article

A Study on IoT Device Authentication Using Artificial Intelligence

Nikos Komninos, Shahram Miri Kelaniki
1 citations
Sensors
Biometric Identification and Security
1.49
article

A Study on IoT Device Authentication Using Artificial Intelligence

Nikos Komninos, Shahram Miri Kelaniki
article en
1 citations

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.

SensorsVol. 25(18)
St George's, University of London (GB), City, University of London (GB)
Openalex Percentile: Top 14%
Biometric Identification and Security
1.49
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