[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content
Springer Nature Link
Log in

Introduction

  • Chapter
  • First Online:
Decentralized Privacy Preservation in Smart Cities

Part of the book series: Wireless Networks ((WN))

  • 142 Accesses

Abstract

In this chapter, we first give an overview of the smart city architecture and applications. Then, we analyze the privacy challenges in smart cities and discuss the motivations and benefits of applying decentralized trust models and approaches to achieve privacy preservation. Finally, we describe the organization of this monograph.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 109.99
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
GBP 139.99
Price includes VAT (United Kingdom)
  • Durable hardcover 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

References

  1. United Nations Department of Economic and Social Affairs, Population Division: Revision of world urbanization prospects (2018). https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html. Accessed 10 May 2023

  2. R. Avtar, S. Tripathi, A.K. Aggarwal, P. Kumar, Population–urbanization–energy nexus: a review. Resources 8(3), 136 (2019)

    Google Scholar 

  3. M. Shahidehpour, Z. Li, M. Ganji, Smart cities for a sustainable urbanization: Illuminating the need for establishing smart urban infrastructures. IEEE Electrif. Mag. 6(2), 16–33 (2018)

    Article  Google Scholar 

  4. K. Zhang, J. Ni, K. Yang, X. Liang, J. Ren, X. Shen, Security and privacy in smart city applications: Challenges and solutions. IEEE Commun. Mag. 55(1), 122–129 (2017)

    Article  Google Scholar 

  5. F. Bélanger, R.E. Crossler, Privacy in the digital age: a review of information privacy research in information systems. MIS Q. 35, 1017–1041 (2011)

    Article  Google Scholar 

  6. V. Moustaka, A. Vakali, L.G. Anthopoulos, A systematic review for smart city data analytics. ACM Comput. Surv. 51(5), 1–41 (2018)

    Article  Google Scholar 

  7. M. Sookhak, H. Tang, Y. He, F.R. Yu, Security and privacy of smart cities: a survey, research issues and challenges. IEEE Commun. Surv. Tutorials 21(2), 1718–1743 (2018)

    Article  Google Scholar 

  8. K. Manheim, L. Kaplan, Artificial intelligence: risks to privacy and democracy. Yale J. Law Technol. 21, 106 (2019)

    Google Scholar 

  9. N. Confessore, Cambridge Analytica and Facebook: The scandal and the fallout so far (2018). https://www.nytimes.com/2018/04/04/us/politics/cambridge-analytica-scandal-fallout.html. Accessed 11 May 2023

  10. International Organization for Standardization, ISO/IEC TS 27570:2021—privacy engineering for system life cycle processes (2021). https://www.iso.org/standard/80201.html

  11. 3rd Generation Partnership Project, 3GPP TS 33.185—security aspect for LTE support of Vehicle-to-Everything (V2X) Services (2022). https://www.3gpp.org/ftp/Specs/archive/33_series/33.185/33185-h00.zip

  12. National Institute of Standards and Technology (NIST), NIST SP 800-144—Guidelines on Security and Privacy in Public Cloud Computing (2011). https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-144.pdf

  13. Official Journal of the European Union, General Data Protection Regulation (2016). https://eur-lex.europa.eu/eli/reg/2016/679/oj

  14. M. Gheisari, H.E. Najafabadi, J.A. Alzubi, J. Gao, G. Wang, A.A. Abbasi, A. Castiglione, OBPP: an ontology-based framework for privacy-preserving in IoT-based smart city. Fut. Gener. Comput. Syst. 123, 1–13 (2021)

    Article  Google Scholar 

  15. P. Kumar, R. Kumar, G. Srivastava, G.P. Gupta, R. Tripathi, T.R. Gadekallu, N.N. Xiong, PPSF: a privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities. IEEE Trans. Netw. Sci. Eng. 8(3), 2326–2341 (2021)

    Article  Google Scholar 

  16. I. Makhdoom, I. Zhou, M. Abolhasan, J. Lipman, W. Ni, PrivySharing: a blockchain-based framework for privacy-preserving and secure data sharing in smart cities. Comput. Secur. 88, 101653 (2020)

    Article  Google Scholar 

  17. M. Shen, X. Tang, L. Zhu, X. Du, M. Guizani, Privacy-preserving support vector machine training over blockchain-based encrypted IoT data in smart cities. IEEE Internet Things J. 6(5), 7702–7712 (2019)

    Article  Google Scholar 

  18. J. Chen, Y. Liu, Y. Xiang, K. Sood, RPPTD: robust privacy-preserving truth discovery scheme. IEEE Syst. J. 16(3), 4525–4531 (2021)

    Article  Google Scholar 

  19. Y. Yu, X. Zeng, X. Xue, J. Ma, LSTM-based intrusion detection system for VANETs: a time series classification approach to false message detection. IEEE Trans. Intell. Transp. Syst. 23(12), 23906–23918 (2022)

    Article  Google Scholar 

  20. J. Keegan, A. Ng, The popular family safety app life360 is selling precise location data on its tens of millions of users (2021). https://themarkup.org/privacy/2021/12/06/the-popular-family-safety-app-life360-is-selling-precise-location-data-on-its-tens-of-millions-of-user. Accessed 15 May 2023

  21. J. Ni, A. Zhang, X. Lin, X. Shen, Security, privacy, and fairness in fog-based vehicular crowdsensing. IEEE Commun. Mag. 55(6), 146–152 (2017)

    Article  Google Scholar 

  22. L. Fang, Y. Li, Z. Liu, C. Yin, M. Li, Z.J. Cao, A practical model based on anomaly detection for protecting medical IoT control services against external attacks. IEEE Trans. Ind. Inform. 17(6), 4260–4269 (2020)

    Article  Google Scholar 

  23. X. Shen, C. Huang, D. Liu, L. Xue, W. Zhuang, R. Sun, B. Ying, Data management for future wireless networks: architecture, privacy preservation, and regulation. IEEE Netw. 35(1), 8–15 (2021)

    Article  Google Scholar 

  24. B. Zhao, K. Fan, K. Yang, Z. Wang, H. Li, Y. Yang, Anonymous and privacy-preserving federated learning with industrial big data. IEEE Trans. Ind. Inform. 17(9), 6314–6323 (2021)

    Article  Google Scholar 

  25. E. Erdin, C. Zachor, M.H. Gunes, How to find hidden users: a survey of attacks on anonymity networks. IEEE Commun. Surv. Tutorials 17(4), 2296–2316 (2015)

    Article  Google Scholar 

  26. C. Huang, J. Ni, R. Lu, X. Shen, Exploring anonymous user reviews: linkability analysis based on machine learning, in Proceedings of IEEE Global Communications Conference (2019), pp. 1–6

    Google Scholar 

  27. Z. Liu, L. Zhang, W. Ni, I.B. Collings, Uncoordinated pseudonym changes for privacy preserving in distributed networks. IEEE Trans. Mobile Comput. 19(6), 1465–1477 (2019)

    Article  Google Scholar 

  28. P.P. Tsang, V.K. Wei, Short linkable ring signatures for e-voting, e-cash and attestation, in Proceedings of International Conference on Information Security Practice and Experience (2005), pp. 48–60

    Google Scholar 

  29. R. Lu, X. Lin, T.H. Luan, X. Liang, X. Shen, Pseudonym changing at social spots: an effective strategy for location privacy in VANETs. IEEE Trans. Veh. Technol. 61(1), 86–96 (2011)

    Article  Google Scholar 

  30. J. Kang, R. Yu, X. Huang, Y. Zhang, Privacy-preserved pseudonym scheme for fog computing supported internet of vehicles. IEEE Trans. Intell. Transp. Syst. 19(8), 2627–2637 (2017)

    Article  Google Scholar 

  31. R. Yu, J. Kang, X. Huang, S. Xie, Y. Zhang, S. Gjessing, MixGroup: accumulative pseudonym exchanging for location privacy enhancement in vehicular social networks. IEEE Trans. Depend. Secure Comput. 13(1), 93–105 (2015)

    Article  Google Scholar 

  32. B. Larsen, T. Giannetsos, I. Krontiris, K. Goldman, Direct anonymous attestation on the road: efficient and privacy-preserving revocation in C-ITS, in Proceedings of ACM Conference on Security and Privacy in Wireless and Mobile Networks (2021), pp. 48–59

    Google Scholar 

  33. K. Yang, L. Chen, Z. Zhang, C.J. Newton, B. Yang, L. Xi, Direct anonymous attestation with optimal TPM signing efficiency. IEEE Trans. Inform. Forensics Secur. 16, 2260–2275 (2021)

    Article  Google Scholar 

  34. D. Liu, H. Wu, C. Huang, J. Ni, X. Shen, Blockchain-based credential management for anonymous authentication in SAGVN. IEEE J. Sel. Areas Commun. 40(10), 3104–3116 (2022)

    Article  Google Scholar 

  35. Y. Li, X. Cao, Y. Yuan, G. Wang, PrivSem: protecting location privacy using semantic and differential privacy. World Wide Web 22, 2407–2436 (2019)

    Article  Google Scholar 

  36. T. Wang, N. Li, S. Jha, Locally differentially private heavy hitter identification. IEEE Trans. Depend. Secure Comput. 18(2), 982–993 (2019)

    Article  Google Scholar 

  37. A. Wood, K. Najarian, D. Kahrobaei, Homomorphic encryption for machine learning in medicine and bioinformatics. ACM Comput. Surv. 53(4), 1–35 (2020)

    Article  Google Scholar 

  38. C. Marcolla, V. Sucasas, M. Manzano, R. Bassoli, F.H. Fitzek, N. Aaraj, Survey on fully homomorphic encryption, theory, and applications. Proc. IEEE 110(10), 1572–1609 (2022)

    Article  Google Scholar 

  39. Y. Zhang, R.H. Deng, S. Xu, J. Sun, Q. Li, D. Zheng, Attribute-based encryption for cloud computing access control: a survey. ACM Comput. Surv. 53(4), 1–41 (2020)

    Google Scholar 

  40. J. Ni, X. Lin, X. Shen, Toward privacy-preserving valet parking in autonomous driving era. IEEE Trans. Veh. Technol. 68(3), 2893–2905 (2019)

    Article  Google Scholar 

  41. D. He, N. Kumar, H. Wang, L. Wang, K.K.R. Choo, A. Vinel, A provably-secure cross-domain handshake scheme with symptoms-matching for mobile healthcare social network. IEEE Trans. Depend. Secure Comput. 15(4), 633–645 (2016)

    Article  Google Scholar 

  42. D. Liu, J. Ni, X. Lin, X. Shen, Transparent and accountable vehicular local advertising with practical blockchain designs. IEEE Trans. Veh. Technol. 69(12), 15694–15705 (2020)

    Article  Google Scholar 

  43. E. Dauterman, V. Fang, N. Crooks, R.A. Popa, Reflections on trusting distributed trust, in Proceedings of ACM Workshop on Hot Topics in Networks (2022), pp. 38–45

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada

    Cheng Huang & Xuemin (Sherman) Shen

Authors
  1. Cheng Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xuemin (Sherman) Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Huang, C., Shen, X.(. (2024). Introduction. In: Decentralized Privacy Preservation in Smart Cities. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-54075-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-54075-2_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-54074-5

  • Online ISBN: 978-3-031-54075-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation