Skip to main content
SpringerLink
Log in

Privacy preservation in the internet of vehicles using local differential privacy and IOTA ledger

  • Published:
Cluster Computing Aims and scope Submit manuscript

A Correction to this article was published on 29 May 2023

This article has been updated

Abstract

With the growth in Vehicular Ad Hoc Network (VANET) technology, many vehicular devices are communicating with each other and with the edge nodes, generating a massive amount of data. One of the biggest challenges is to preserve users’ privacy as the data hold personal and sensitive information, which upon leakage could have disastrous consequences. Privacy preservation has gained remarkable consideration by companies as a notable number of users have started being conscious about privacy protection of their data. Most privacy preserving solutions that have been developed in such a distributed scenario need a third party for data anonymization. In a system of public data sharing, one of the most popular and useful anonymization techniques is Local Differential Privacy (LDP). LDP allows users to anonymize their data locally and individually and does not need a third party for data anonymization, resulting in stronger privacy guarantees. In this work, firstly, considering the security and privacy threats posed by untrusted third parties, namely edge nodes or roadside units (RSUs), we provide a privacy preservation solution for VANETs using LDP, eliminating the need for a third party to anonymize sensitive vehicular data. Secondly, to provide a tier 2 privacy and security, we introduce a model that uses IOTA ledger on top of the LDP perturbation technique. Consequently, not only does our model achieve privacy, but tier 2 privacy preservation method based on IOTA ledger provides immutability, scalability, and quantum secrecy over a largely complex and distributed network of vehicles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data availability

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Change history

Notes

  1. kaggle.com/eron93br/obd2data.

References

  1. Al-Shareeda, M.A., Anbar, M., Manickam, S., Yassin, A.A.: VPPCS: VANET-based privacy-preserving communication scheme. IEEE Access 8, 150914–150928 (2020)

    Article  Google Scholar 

  2. Ghaith, I.H., Rawashdeh, A., Al Zubi, S.: Transfer learning in data fusion at autonomous driving. In: 2021 International Conference on Information Technology (ICIT), IEEE. pp. 714–718 (2021).

  3. Alkhatib, A.A., Abu Maria, K., Alzu’bi, S., Abu Maria, E.: Novel system for road traffic optimisation in large cities. IET Smart Cities 4(2), 143–155 (2022)

    Article  Google Scholar 

  4. Elbes, M., Alrawashdeh, T., Almaita, E., AlZu’bi, S., Jararweh, Y.: A platform for power management based on indoor localization in smart buildings using long short-term neural networks. Trans. Emerg. Telecommun. Technol. 33(3), 3867 (2022)

    Article  Google Scholar 

  5. Al-Shareeda, M.A., Anbar, M., Hasbullah, I.H., Manickam, S., Hanshi, S.M.: Efficient conditional privacy preservation with mutual authentication in vehicular ad hoc networks. IEEE Access 8, 144957–144968 (2020)

    Article  Google Scholar 

  6. Sehrish, S., Masoom, A., Abid, K.: Privacy aware decentralized access control. Future Gener. Comput. Syst. 101, 420–433 (2019)

    Article  Google Scholar 

  7. Umair, S., Masoom, A., Sherali, Z., Abid, K.: Privacy aware iota ledger: decentralized mixing and unlinkable iota transactions. Comput. Netw. 148, 361–372 (2019)

    Article  Google Scholar 

  8. Wang, J., Zhang, Y., Gu, X.: Trust-aware privacy-preserving scheme for VANET. Comput. Eng. Appl. 06, 1 (2018)

    Google Scholar 

  9. Wang, J., Cai, Z., Yu, J.: Achieving personalized \$ k \$-anonymity-based content privacy for autonomous vehicles in CPS. IEEE Trans. Ind. Inf. 16(6), 4242–4251 (2019)

    Article  Google Scholar 

  10. Zhang, S., Li, X., Tan, Z., Peng, T., Wang, G.: A caching and spatial k-anonymity driven privacy enhancement scheme in continuous location-based services. Future Gener. Comput. Syst. 94, 40–50 (2019)

    Article  Google Scholar 

  11. Bebensee, B.: Local differential privacy: a tutorial. arXiv:1907.11908 (2019)

  12. Zhao, P., Zhang, G., Wan, S., Liu, G., Umer, T.: A survey of local differential privacy for securing internet of vehicles. J. Supercomput. 76, 1–22 (2019)

    Google Scholar 

  13. Raja, G., Anbalagan, S., Vijayaraghavan, G., Dhanasekaran, P., Al-Otaibi, Y.D., Bashir, A.K.: Energy-efficient end-to-end security for software defined vehicular networks. IEEE Trans. Ind. Inf. 17(8), 5730–5737 (2020)

    Article  Google Scholar 

  14. Hassija, V., Chamola, V., Gupta, V., Chalapathi, G.S.: A framework for secure vehicular network using advanced blockchain. In: 2020 International Wireless Communications and Mobile Computing (IWCMC), pp. 1260–1265 (2020). IEEE

  15. Erlingsson, U., Pihur, V., Korolova, A.: Rappor: Randomized aggregatable privacy-preserving ordinal response. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1054–1067 (2014)

  16. Team, A., et al.: Learning with privacy at scale. Appl. Mach. Learn. J 1(9) (2017)

  17. Ding, B., Kulkarni, J., Yekhanin, S.: Collecting telemetry data privately. In: Advances in Neural Information Processing Systems, pp. 3571–3580 (2017)

  18. Wang, T., Zheng, Z., Rehmani, M.H., Yao, S., Huo, Z.: Privacy preservation in big data from the communication perspective-a survey. IEEE Commun. Surv. Tutor. 21(1), 753–778 (2018)

    Article  Google Scholar 

  19. Hassan, M.U., Rehmani, M.H., Chen, J.: Differential privacy techniques for cyber physical systems: a survey. IEEE Commun. Surv. Tutor. 22(1), 746–789 (2019)

    Article  Google Scholar 

  20. Tesei, A., Di Mauro, L., Falcitelli, M., Noto, S., Pagano, P.: Iota-vpki: a dlt-based and resource efficient vehicular public key infrastructure. In: 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), pp. 1–6 (2018). IEEE

  21. Ghane, S., Jolfaei, A., Kulik, L., Ramamohanarao, K., Puthal, D.: Preserving privacy in the internet of connected vehicles. IEEE Trans. Intell. Transp. Syst. 22(8), 5018–5027 (2020)

    Article  Google Scholar 

  22. Bartolomeu, P.C., Vieira, E., Ferreira, J.: Iota feasibility and perspectives for enabling vehicular applications. In: 2018 IEEE Globecom Workshops (GC Wkshps), pp. 1–7 (2018). IEEE

  23. Vijayakumar, P., Chang, V., Deborah, L.J., Balusamy, B., Shynu, P.: Computationally efficient privacy preserving anonymous mutual and batch authentication schemes for vehicular ad hoc networks. Future Gener. Comput. Syst. 78, 943–955 (2018)

    Article  Google Scholar 

  24. Arif, M., Chen, J., Wang, G., Geman, O., Balas, V.E.: Privacy preserving and data publication for vehicular trajectories with differential privacy. Measurement 173, 108675 (2021)

    Article  Google Scholar 

  25. Chen, X., Zhang, T., Shen, S., Zhu, T., Xiong, P.: An optimized differential privacy scheme with reinforcement learning in VANET. Comput. Secur. 110, 102446 (2021)

    Article  Google Scholar 

  26. Naresh, V.S., Allavarpu, V.D., Reddi, S.: Blockchain iota sharding based scalable secure group communication in large VANETs. IEEE Internet Things J. 10, 5205–5213 (2022)

    Article  Google Scholar 

  27. Faccia, A.: Quantum Finance. Opportunities and threats (2020)

  28. De Roode, G., Ullah, I., Havinga, P.J.: How to break iota heart by replaying? In: 2018 IEEE Globecom Workshops (GC Wkshps), pp. 1–7 (2018). IEEE

  29. Hayward, M.: Quantum Computing and Shor’s Algorithm. Macquarie University Mathematics Department, Sydney (2008)

    Google Scholar 

  30. Zhao, L., Li, X., Gu, B., Zhou, Z., Mumtaz, S., Frascolla, V., Gacanin, H., Ashraf, M.I., Rodriguez, J., Yang, M., et al.: Vehicular communications: standardization and open issues. IEEE Commun. Stand. Magn. 2(4), 74–80 (2018)

    Article  Google Scholar 

  31. Popov, S.: The tangle. White Paper 1, 3 (2018)

    Google Scholar 

  32. Iftikhar, Z., Javed, Y., Zaidi, S.Y.A., Shah, M.A., IqbalKhan, Z., Mussadiq, S., Abbasi, K.: Privacy preservation in resource-constrained IoT devices using blockchain-a survey. Electronics 10(14), 1732 (2021)

    Article  Google Scholar 

  33. AlZu’bi, S., Jararweh, Y.: Data fusion in autonomous vehicles research, literature tracing from imaginary idea to smart surrounding community. In: 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC), pp. 306–311 (2020). IEEE

  34. Iftikhar, Z., Iftikhar, M., Shah, M.A.: Quantum safe cloud computing using hash-based digital signatures. In: 2021 26th International Conference on Automation and Computing (ICAC), pp. 1–6 (2021). IEEE

Download references

Funding

No funding has been received for this paper.

Author information

Authors and Affiliations

  1. Department of Computer Science, COMSATS University Islamabad, Islamabad, 44000, Pakistan

    Zainab Iftikhar & Munam Ali Shah

  2. Institute of Information Technology, Quaid i Azam University, Islamabad, 44000, Pakistan

    Adeel Anjum

  3. College of Science and Engineering, University of Derby, Derby, DE22 1GB, UK

    Abid Khan

  4. Department of Embedded Systems Engineering, Incheon National University, Incheon, 22012, Republic of Korea

    Gwanggil Jeon

  5. Energy Excellence & Smart City Lab., Incheon National University, Incheon, 22012, Republic of Korea

    Gwanggil Jeon

Authors
  1. Zainab Iftikhar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adeel Anjum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abid Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Munam Ali Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gwanggil Jeon
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ZI: software, validation, writing, visualization. AA: conceptualization, software, validation. AK: methodology, visualization, investigation. MAS: software, writing, Visualization, investigation. GJ: validation, data curation, reviewing and editing, reviewing and editing.

Corresponding author

Correspondence to Gwanggil Jeon.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: The author name Gwanggil Jeon has been corrected.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Iftikhar, Z., Anjum, A., Khan, A. et al. Privacy preservation in the internet of vehicles using local differential privacy and IOTA ledger. Cluster Comput 26, 3361–3377 (2023). https://doi.org/10.1007/s10586-023-04002-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-023-04002-0

Keywords

Search

Navigation