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Article | Open Access

A Novel Signature-Based Secure Intrusion Detection for Smart Transportation Systems

Hanaa Nafea1Awais Qasim2Sana Abdul Sattar2Adeel Munawar3Muhammad Nadeem Ali4Byung-Seo Kim4( )
College of Computer Science and Engineering, Taibah University, Al-Madinah Al-Munawwarah, 42353, Saudi Arabia
Department of Computer Science, GC University Lahore, Lahore, 54000, Pakistan
Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12121, Thailand
Department of Software and Communication Engineering, Hongik University, Sejong-City, 30016, Republic of Korea
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Abstract

The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats, making intrusion detection a critical aspect of ensuring their secure operation. Traditional intrusion detection systems have limitations in terms of centralized architecture, lack of transparency, and vulnerability to single points of failure. This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems. This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signature-based intrusion detection system. The introduced signature facilitates accurate detection and systematic classification of attacks, enabling categorization according to their severity levels within the transportation infrastructure. Through comparative analysis, the research demonstrates that the blockchain-based IDS outperforms traditional approaches in terms of security, resilience, and data integrity.

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Computers, Materials & Continua
Article number: 54

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Cite this article:
Nafea H, Qasim A, Sattar SA, et al. A Novel Signature-Based Secure Intrusion Detection for Smart Transportation Systems. Computers, Materials & Continua, 2026, 86(3): 54. https://doi.org/10.32604/cmc.2025.072281

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Received: 23 August 2025
Accepted: 29 October 2025
Published: 12 January 2026
© The Author 2025.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.