A novel blockchain-integrated IoT framework for secure and efficient vehicle-to-infrastructure communication in smart transportation
The rapid integration of the Internet of Things (IoT) into intelligent transportation systems is revolutionizing urban mobility through real-time data connectivity between vehicles and infrastructure. However, security issues, data integrity, and network congestion are major challenges not conducive...
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| Vydáno v: | Peer-to-peer networking and applications Ročník 18; číslo 6; s. 324 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
Springer US
01.10.2025
Springer Nature B.V |
| Témata: | |
| ISSN: | 1936-6442, 1936-6450 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The rapid integration of the Internet of Things (IoT) into intelligent transportation systems is revolutionizing urban mobility through real-time data connectivity between vehicles and infrastructure. However, security issues, data integrity, and network congestion are major challenges not conducive to IoT can be operated in harmony smart transportation. Conventional centralized communication models face the risk of exposing critical transportation data to cyberattacks, unauthorized access, and single points of failure accessibility, ultimately compromising the system’s reliability. This work presents a new framework for IoT-blockchain-based smart transportation networks to facilitate secure, scalable, and efficient vehicle-to-infrastructure (V2I) communication. The proposed method is also writing on a very limited state, by this way transmit light data with low latency using a blockchain that supports a very light and decentralized architecture in the sense of usage of edge computing. Blockchain consensus mechanisms, including Proof-of-Authority (PoA), could render energy-intensive mining unnecessary, thereby guaranteeing data authenticity and tamper-proof transactions. In addition, a multi-level encryption scheme is also adopted to limit the access of unauthorized users and enhance the privacy protection in V2I communication. The paper presents the design of a network security model that employs real-time anomaly detection algorithms and self-adaptive machine learning techniques for the purpose of dynamically detecting security threats and improving traffic flow management. Compared to traditional centralized models, the proposed framework increases the data security by 45%, reduces the latency of the V2I communication by 35%, and increases the overall network efficiencies by 50%. In addition, the intelligent resource allocation mechanism alleviates network congestion by 40% and ensures the priority of important data packets. By providing an extremely robust, distributed, and self-adjusting communication model for smart cities, this research bridges an important gap for IoT-based transportation resilience and reliability. These findings provide a game-changing approach to accelerating the safety, reliability, and sustainability of next-gen transportation ecosystems while minimizing cyber risk in the connected. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1936-6442 1936-6450 |
| DOI: | 10.1007/s12083-025-02119-0 |