A Blockchain-Enabled Framework for Privacy Preserving ‎Smart Mobility Services

  • Authors

    https://doi.org/10.14419/4ve8yy06

    Received date: December 31, 2025

    Accepted date: January 24, 2026

    Published date: January 26, 2026

  • Blockchain; Privacy Preservation; Geo-indistinguishability; Smart Mobility; Vehicular Networks; Zero-Knowledge Proofs; Proof-of-Authority; ‎Energy Efficiency; Cybersecurity; Smart Cities

  • Abstract

    Smart mobility services generate large volumes of sensitive location and identity data, raising critical concerns related to privacy leakage, ‎security vulnerabilities, and trust in large-scale urban deployments. To address these challenges, this paper proposes a blockchain-based ‎privacy-preserving framework for smart mobility services that integrates geo-indistinguishability, pseudonymous authentication, Zero-‎Knowledge Proofs (ZKPs), and Proof-of-Authority (PoA) consensus into a unified architecture. The framework ensures end-to-end privacy ‎by combining calibrated location obfuscation with decentralized transaction validation and immutable auditability, thereby mitigating both ‎inference-based attacks and reliance on centralized trust.‎

    The proposed framework was evaluated using the TAPAS Cologne mobility dataset, comprising 1,000 simulated vehicles and 20 block-‎chain validators. Experimental results demonstrate that adversarial inference accuracy is reduced to below 12%, while approximately 75% ‎navigation utility is preserved at balanced privacy budgets. Security analysis confirms robust protection against tracking, replay, Sybil, and ‎collusion attacks, with replay attack success rates reduced from 70% to 2% through the enforcement of timestamps and nonces, along with ‎cryptographic verification.‎

    Performance evaluation demonstrates that the framework achieves high throughput (1,200 transactions per second) with sub-second latency ‎‎(0.8 seconds) under realistic transaction loads. Storage growth is optimized to 2.1 GB per million transactions, and the PoA consensus ‎mechanism achieves approximately 30% lower energy consumption compared to Proof-of-Stake-based designs. In addition, resilience ex-‎periments confirm Byzantine fault tolerance under up to 30% malicious validator participation, without service degradation.‎

    Overall, the results demonstrate the practical feasibility of deploying the proposed framework in real-world smart mobility ecosystems that ‎require simultaneous privacy preservation, scalability, and energy efficiency. The framework represents a significant step toward trustwor-‎thy, privacy-aware, and sustainable smart-city mobility infrastructure, providing a robust foundation for next-generation decentralized mo-‎bility services‎.

  • References

    1. H. Al-Balasmeh, M. Singh, and R. Singh, “Framework of data privacy preservation and location obfuscation in vehicular cloud networks,” Concur-rency and Computation: Practice and Experience, vol. 33, no. 21, Art. no. e6482, 2021, https://doi.org/10.1002/cpe.6482.
    2. H. Al-Balasmeh, M. Singh, and R. Singh, “Framework of geofence service using dummy location privacy preservation in vehicular cloud network,” Int. Arab J. Inf. Technol., vol. 19, no. 4, pp. 543–552, 2022.
    3. H. Al-Balasmeh, M. Singh, and R. Singh, “Data and location privacy of smart devices over vehicular cloud computing,” in Proc. 35th FRUCT Conf. Wireless and Mobile Computing, IEEE, 2024, pp. 239–246.
    4. H. Al-Balasmeh, “Dummy location privacy preservation in vehicular cloud networks,” J. Inf. Secur., vol. 11, no. 4, pp. 233–245, 2022.
    5. M. E. Andrés, N. E. Bordenabe, K. Chatzikokolakis, and C. Palamidessi, “Geo-indistinguishability: Differential privacy for location-based sys-tems,” in Proc. 20th ACM Conf. Computer and Communications Security (CCS), New York, NY, USA, 2013, pp. 901–914, https://doi.org/10.1145/2508859.2516735.
    6. Y. Bai, S. Lee, and S. H. Seo, “A survey on directed acyclic graph-based blockchain in smart mobility,” Sensors, vol. 25, no. 7, Art. no. 3221, 2025, https://doi.org/10.3390/s25041108.
    7. R. García, F. Liu, and X. Chen, “Privacy-preserving authentication in IoT-enabled mobility services: A layered approach,” IEEE Trans. Intell. Transp. Syst., vol. 25, no. 3, pp. 2889–2902, 2024.
    8. R. D. García et al., “A survey of blockchain-based privacy applications,” arXiv preprint, arXiv:2401.04567, 2024. [Online]. Available: https://arxiv.org/abs/2401.04567.
    9. A. Hannemann and E. Buchmann, “Is homomorphic encryption feasible for smart mobility?” arXiv preprint, arXiv:2304.07845, 2023. [Online]. Available: https://arxiv.org/abs/2304.07845.
    10. M. Islam, F. Zhou, and R. Kaur, “Decentralized trust framework for smart cities: A blockchain-enabled cybersecurity and data integrity model,” Sci. Rep., vol. 15, Art. no. 11221, 2025, https://doi.org/10.1038/s41598-025-06405-y.
    11. A. Miron, P. Zhang, and H. Lee, “Integrating blockchain technology into Mobility-as-a-Service platforms for smart cities,” Smart Cities, vol. 8, no. 2, pp. 87–101, 2025, https://doi.org/10.3390/smartcities8010009.
    12. A. Miron, P. Zhang, and H. Lee, “Blockchain-enabled Mobility-as-a-Service: Trust, payments, and scalability,” IEEE Access, vol. 13, pp. 22201–22214, 2025.
    13. S. Narkedimilli et al., “FAPL-DM-BC: A secure and scalable federated learning framework with adaptive privacy, dynamic masking, blockchain, and XAI for the Internet of Vehicles,” arXiv preprint, arXiv:2501.01422, 2025. [Online]. Available: https://arxiv.org/abs/2501.01422.
    14. J. Xu, Y. Chen, and L. Wang, “Zero-knowledge proofs for secure and privacy-preserving authentication in vehicular networks,” IEEE Trans. Veh. Technol., vol. 68, no. 10, pp. 9359–9372, 2019.
    15. X. Xu, I. Weber, and M. Staples, Architecture for Blockchain Applications. Cham, Switzerland: Springer, 2019.
    16. Y. Zhang and H. Lee, “Pseudonym-based authentication for privacy in vehicular cloud environments,” IEEE Internet Things J., vol. 8, no. 7, pp. 5560–5572, 2021, https://doi.org/10.1109/JIOT.2021.3068410.
    17. J. Zhou, Y. Zhang, and S. Wang, “Blockchain for secure data management in smart cities,” IEEE Commun. Surveys Tuts., vol. 22, no. 2, pp. 1765–1790, 2020.
    18. Y. Zhou, Z. Xu, and N. N. Xiong, “The privacy-preserving blockchain for Internet of Vehicles: Challenges and opportunities,” IEEE Network, vol. 34, no. 6, pp. 154–161, 2020.

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  • How to Cite

    Al-Balasmeh, H., Jaber , F. A. ., & Abdulsattar , S. S. . (2026). A Blockchain-Enabled Framework for Privacy Preserving ‎Smart Mobility Services. International Journal of Basic and Applied Sciences, 15(1), 148-160. https://doi.org/10.14419/4ve8yy06