Skip to main content

A Blockchain-Based Architecture to Manage User Privacy Preferences on Smart Shared Spaces Privately

  • Conference paper
  • First Online:
Data Privacy Management, Cryptocurrencies and Blockchain Technology (DPM 2022, CBT 2022)

Abstract

Smart shared spaces, such as smart buildings, represent a fast-growing market and can benefit from several sensors that generate data which can be used to improve automatisation, increase efficiency in energy management, and optimise occupant’s comfort. Equally, the smart shared spaces pose many privacy challenges as they are equipped with sensors that can potentially be used to gather data about occupants that they may or may not feel comfortable disclosing, for example, details of their daily routine or occupancy reports of their office. Due to these challenges, it can lead to the opposite results to the optimisation of occupant’s comfort as occupants may not want to use the space due to the privacy concerns. Therefore, it is important to allow the occupants to inform their privacy settings so they feel more confident knowing that their privacy preferences are being respected. We recognise that in some spaces (e.g., shared workplaces) occupants may feel uncomfortable disclosing their preferences if their anonymity is not respected due to the lack of transparency about who can control that data. Thus, this work focuses on a decentralised system based on the SITA privacy model to provide occupants of shared spaces a way to specify and manage their privacy preferences anonymously. We propose a blockchain solution through smart contracts to control how the privacy settings are shared, ensuring that the users have full control of these records. Moreover, it allows traceability over the user’s preferences data usage. Our evaluation shows that the system performs well in regard to time and usability and it can be linked to different smart building management systems. Consequently, this work demonstrates data protection in practice as it puts in place an appropriate technical and organisational measure to safeguard the individual’s privacy by increasing transparency and accountability of smart building data management in accordance to the data protection by design and default approach under the General Data Protection Regulations (GDPR).

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://nvlpubs.nist.gov/nistpubs/fips/nist.fips.197.pdf.

  2. 2.

    https://csrc.nist.gov/publications/detail/fips/202/final.

  3. 3.

    MetaMask extension is available at https://metamask.io.

  4. 4.

    https://github.com/cvncodes/DPM2022.

  5. 5.

    Exchange Rate from July 11, 2022 at 1AM availabe at https://coinmarketcap.com/.

References

  1. Alharby, M., Castagna Lunardi, R., Aldweesh, A., van Moorsel, A.: Data-driven model-based analysis of the ethereum verifier’s dilemma. In: 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 209–220 (2020). https://doi.org/10.1109/DSN48063.2020.00038

  2. Bugeja, J., Jacobsson, A., Davidsson, P.: On privacy and security challenges in smart connected homes. In: 2016 European Intelligence and Security Informatics Conference (EISIC), pp. 172–175 (2016). https://doi.org/10.1109/EISIC.2016.044

  3. Cejka, S., Knorr, F., Kintzler, F.: Privacy issues in smart buildings by examples in smart metering. In: 25th International Conference on Electricity Distribution (CIRED) (2019)

    Google Scholar 

  4. European Commission, D.G.f.R., Innovation, Renda, A.S.S.S.T.D.e.a.: Industry 5.0, a transformative vision for europe: governing systemic transformations towards a sustainable industry. Publications Office of the European Union (2022). https://data.europa.eu/doi/10.2777/17322

  5. European Parliament, Directorate-General for Internal Policies of the Union, G.F.: Industry 4.0, European parliament. Publications Office (2017). https://data.europa.eu/doi/10.2861/085601

  6. European Union (EU): Regulation (EU) 2016/679 of the European parliament and of the council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing directive 95/46/ec (general data protection regulation) (2016). https://eur-lex.europa.eu/eli/reg/2016/679/oj

  7. G. Zyskind, O.N., Pentland, A.S.: Decentralizing privacy: using blockchain to protect personal data. In: 2015 IEEE CS Security and Privacy Workshops, pp. 180–184 (2015). https://doi.org/10.1109/SPW.2015.27

  8. Harper, S., Mehrnezhad, M., Mace, J.: On privacy and security challenges in smart connected homes. In: 2016 European Intelligence and Security Informatics Conference (EISIC), pp. 172–175 (2016). https://doi.org/10.1109/EISIC.2016.044

  9. Harper, S., Mehrnezhad, M., Mace, J.C.: User privacy concerns and preferences in smart buildings. In: Groß, T., Viganò, L. (eds.) STAST 2020. LNCS, vol. 12812, pp. 85–106. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79318-0_5

    Chapter  Google Scholar 

  10. Khalil, N., Benhaddou, D., Gnawali, O., Subhlok, J.: Nonintrusive occupant identification by sensing body shape and movement. In: Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments, pp. 1–10. Association for Computing Machinery, New York, NY, USA (2016). https://doi.org/10.1145/2993422.2993429

  11. Lax, G., Russo, A., Fascì, L.S.: A blockchain-based approach for matching desired and real privacy settings of social network users. Inf. Sci. 557, 220–235 (2021). https://doi.org/10.1016/j.ins.2021.01.004, https://www.sciencedirect.com/science/article/pii/S0020025521000050

  12. Li, T., Wang, H., He, D., Yu, J.: Blockchain-based privacy-preserving and rewarding private data sharing for IoT. IEEE Internet Things J. 14(8), 1–12 (2022). https://doi.org/10.1109/JIOT.2022.3147925

    Article  Google Scholar 

  13. Lunardi, R.C., Alharby, M., Nunes, H.C., Dong, C., Zorzo, A.F., van Moorsel, A.: Context-based consensus for appendable-block blockchains. In: 2020 IEEE International Conference on Blockchain (Blockchain), pp. 401–408 (2020)

    Google Scholar 

  14. Lunardi, R.C., Michelin, R.A., Neu, C.V., Zorzo, A.F.: Distributed access control on IoT ledger-based architecture. In: 2018 IEEE/IFIP Network Operations and Management Symposium (NOMS), pp. 1–7 (2018)

    Google Scholar 

  15. Lunardi, R.C., Michelin, R.A., Neu, C.V., Nunes, H.C., Zorzo, A.F., Kanhere, S.S.: Impact of consensus on appendable-block blockchain for IoT. In: 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous), pp. 228–237. Association for Computing Machinery (2019)

    Google Scholar 

  16. Andersen, M.S., Kjargaard, M.B., Grønbæk, K.: The SITA principle for location privacy - conceptual model and architecture. In: International Conference on Privacy and Security in Mobile Systems (PRISMS), pp. 1–8 (2013). https://doi.org/10.1109/PRISMS.2013.6927184

  17. Pappachan, P., et al.: Towards privacy-aware smart buildings: capturing, communicating, and enforcing privacy policies and preferences. In: IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 193–198 (2017). https://doi.org/10.1109/ICDCSW.2017.52

  18. Rudolph, M., Polst, S., Doerr, J.: Enabling users to specify correct privacy requirements. In: Knauss, E., Goedicke, M. (eds.) REFSQ 2019. LNCS, vol. 11412, pp. 39–54. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-15538-4_3

    Chapter  Google Scholar 

  19. Schomakers, EM., L.C.Z.M.: All of me? users’ preferences for privacy-preserving data markets and the importance of anonymity. Electron Markets 30, 649–655 (2020). https://doi.org/10.1007/s12525-020-00404-9, https://link.springer.com/article/10.1007/s12525-020-00404-9

  20. Stellios, I., Mokos, K., Kotzanikolaou, P.: Assessing vulnerabilities and IoT-enabled attacks on smart lighting systems. In: Katsikas, S., et al. (eds.) ESORICS 2021. LNCS, vol. 13106, pp. 199–217. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-95484-0_13

    Chapter  Google Scholar 

  21. Včelák, J., Vodička, A., Maška, M., Mrňa, J.: Smart building monitoring from structure to indoor environment. In: 2017 Smart City Symposium Prague (SCSP), pp. 1–5 (2017). https://doi.org/10.1109/SCSP.2017.7973859

  22. Zhang, L., Lee, B., Ye, Y., Qiao, Y.: Evaluation of ethereum end-to-end transaction latency. In: 2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS), pp. 1–5 (2021). https://doi.org/10.1109/NTMS49979.2021.9432676

  23. Zyskind, G., Nathan, O., Pentland, A.S.: Decentralizing privacy: using blockchain to protect personal data. In: Proceedings - 2015 IEEE Security and Privacy Workshops, SPW 2015, pp. 180–184 (2015)

    Google Scholar 

Download references

Acknowledgement

This work has been supported by the PETRAS National Centre of Excellence for IoT Systems Cybersecurity, which has been funded by the UK EPSRC under grant number EP/S035362/1. Roben C. Lunardi is funded by IFRS.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Charles V. Neu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Neu, C.V., Gibson, J., Lunardi, R.C., Leesakul, N., Morisset, C. (2023). A Blockchain-Based Architecture to Manage User Privacy Preferences on Smart Shared Spaces Privately. In: Garcia-Alfaro, J., Navarro-Arribas, G., Dragoni, N. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM CBT 2022 2022. Lecture Notes in Computer Science, vol 13619. Springer, Cham. https://doi.org/10.1007/978-3-031-25734-6_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-25734-6_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-25733-9

  • Online ISBN: 978-3-031-25734-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics