Skip to main content
SpringerLink
Log in
Book cover

International Conference on Information and Communications Security

ICICS 2022: Information and Communications Security pp 221–239Cite as

Lightweight and Practical Privacy-Preserving Image Masking in Smart Community

  • 1119 Accesses

Part of the Lecture Notes in Computer Science book series (LNCS,volume 13407)

Abstract

Advances in the Internet of Things (IoT) and telecommunications technologies (e.g., 5G) have contributed to the development of smart cities and nations (collectively referred to as smart communities). In a smart community, IoT devices can collect significant information about urban residents (e.g., a large number of images collected by cameras containing sensitive information), and such information may be shared with intermediate nodes. In real-world deployment, intermediate nodes are not completely trusted, where the information collected may be used for commercial purposes (e.g., user profiling and advertising) or malicious activities (e.g., covert surveillance). In this paper, we introduce an approach to ensure privacy-preserving image masking. Specifically, before the image is transmitted to the camera owner or the monitoring cloud platform, only sensitive areas instead of the entire image will be processed according to the camera owner’s settings, which allows to significantly reduce the computational cost. Then, in order to reduce the interactions between the community data center and the IoT camera, the monitoring cloud platform performs proxy re-encryption. This allows the community data center to recover the original image without relying on the IoT device’s private key. Our evaluation indicates the utility and efficiency of our approach, as compared with similar schemes.

Keywords

  • Smart community
  • Proxy re-encryption
  • Privacy preservation
  • Image masking

Supported in part by the Natural Science Foundation of China under Grant 62072133, in part by the Key Projects of Guangxi Natural Science Foundation under Grant 2018GXNSFDA281040, in part by the Innovation Project of Guangxi Graduate Education under Grant YCSW2022279.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
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

Learn about institutional subscriptions

References

  1. Boccardi, F., Heath, R.W., Lozano, A., Marzetta, T.L., Popovski, P.: Five disruptive technology directions for 5G. IEEE Commun. Mag. 52(2), 74–80 (2014). https://doi.org/10.1109/MCOM.2014.6736746

    CrossRef  Google Scholar 

  2. Chen, Z., Zhu, T., Wang, C., Ren, W., Xiong, P.: GAN-based image privacy preservation: balancing privacy and utility. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds.) ML4CS 2020. LNCS, vol. 12486, pp. 287–296. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-62223-7_24

    CrossRef  Google Scholar 

  3. De Santis, F., Schauer, A., Sigl, G.: Chacha20-poly1305 authenticated encryption for high-speed embedded IoT applications. In: Design, Automation Test in Europe Conference Exhibition (DATE 2017), pp. 692–697 (2017). https://doi.org/10.23919/DATE.2017.7927078

  4. Dhall, S., Pal, S.K., Sharma, K.: A chaos-based multi-level dynamic framework for image encryption. In: Alam, M., Shakil, K.A., Khan, S. (eds.) Internet of Things (IoT), pp. 189–217. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-37468-6_10

    CrossRef  Google Scholar 

  5. Green, M., Ateniese, G.: Identity-based proxy re-encryption. In: Katz, J., Yung, M. (eds.) ACNS 2007. LNCS, vol. 4521, pp. 288–306. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72738-5_19

    CrossRef  Google Scholar 

  6. Gu, G., Ling, J.: A fast image encryption method by using chaotic 3D cat maps. Optik 125(17), 4700–4705 (2014). https://doi.org/10.1016/j.ijleo.2014.05.023, https://www.sciencedirect.com/science/article/pii/S0030402614005993

  7. Guan, Z., Li, J., Huang, L., Xiong, X., Liu, Y., Cai, S.: A novel and fast encryption system based on improved Josephus scrambling and chaotic mapping. Entropy 24(3) (2022). https://doi.org/10.3390/e24030384, https://www.mdpi.com/1099-4300/24/3/384

  8. Horé, A., Ziou, D.: Image quality metrics: PSNR vs. SSIM. In: 2010 20th International Conference on Pattern Recognition, pp. 2366–2369 (2010). https://doi.org/10.1109/ICPR.2010.579

  9. Hua, Z., Zhou, Y., Huang, H.: Cosine-transform-based chaotic system for image encryption. Inf. Sci. 480, 403–419 (2019). https://doi.org/10.1016/j.ins.2018.12.048, https://www.sciencedirect.com/science/article/pii/S0020025518309927

  10. Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image/video quality assessment. Electron. Lett. 44(13), 800–801 (2008)

    CrossRef  Google Scholar 

  11. Jan, M.A., Zhang, W., Usman, M., Tan, Z., Khan, F., Luo, E.: SmartEdge: an end-to-end encryption framework for an edge-enabled smart city application. J. Netw. Comput. Appl. 137, 1–10 (2019). https://doi.org/10.1016/j.jnca.2019.02.023, https://www.sciencedirect.com/science/article/pii/S1084804519300827

  12. Li, T., Zhang, D.: Hyperchaotic image encryption based on multiple bit permutation and diffusion. Entropy 23(5), 510 (2021). https://doi.org/10.3390/e23050510, https://www.mdpi.com/1099-4300/23/5/510

  13. Li, X., Lu, R., Liang, X., Shen, X., Chen, J., Lin, X.: Smart community: an internet of things application. IEEE Commun. Mag. 49(11), 68–75 (2011). https://doi.org/10.1109/MCOM.2011.6069711

    CrossRef  Google Scholar 

  14. Liu, W., Sun, K., Zhu, C.: A fast image encryption algorithm based on chaotic map. Opt. Lasers Eng. 84, 26–36 (2016). https://doi.org/10.1016/j.optlaseng.2016.03.019

    CrossRef  Google Scholar 

  15. Maisheri, C., Sharma, D.: Enabling indirect mutual trust for cloud storage systems. Int. J. Comput. Appl. 82(2), 1–11 (2013). https://doi.org/10.5120/14085-0768

    CrossRef  Google Scholar 

  16. Meng, L., Yin, S., Zhao, C., Li, H., Sun, Y.: An improved image encryption algorithm based on chaotic mapping and discrete wavelet transform domain. Int. J. Netw. Secur. 22(1), 155–160 (2020)

    Google Scholar 

  17. Mondal, B., Singh, J.P.: A lightweight image encryption scheme based on chaos and diffusion circuit. Multimedia Tools Appl. 1–25 (2021)

    Google Scholar 

  18. Muhammad, K., Hamza, R., Ahmad, J., Lloret, J., Wang, H., Baik, S.W.: Secure surveillance framework for IoT systems using probabilistic image encryption. IEEE Trans. Industr. Inf. 14(8), 3679–3689 (2018). https://doi.org/10.1109/TII.2018.2791944

    CrossRef  Google Scholar 

  19. Naseer, Y., Shah, T., Shah, D.: A novel hybrid permutation substitution base colored image encryption scheme for multimedia data. J. Inf. Secur. Appl. 59, 102829 (2021). https://doi.org/10.1016/j.jisa.2021.102829, https://www.sciencedirect.com/science/article/pii/S221421262100065X

  20. Preishuber, M., Hütter, T., Katzenbeisser, S., Uhl, A.: Depreciating motivation and empirical security analysis of chaos-based image and video encryption. IEEE Trans. Inf. Forensics Secur. 13(9), 2137–2150 (2018). https://doi.org/10.1109/TIFS.2018.2812080

    CrossRef  Google Scholar 

  21. Rajendran, S., Doraipandian, M.: Chaos based secure medical image transmission model for IoT- powered healthcare systems. In: IOP Conference Series: Materials Science and Engineering, vol. 1022, no. 1, p. 012106 (2021). https://doi.org/10.1088/1757-899x/1022/1/012106

  22. Harichandana, B.S.S., Agarwal, V., Ghosh, S., Ramena, G., Kumar, S., Raja, B.R.K.: PrivPAS: a real time privacy-preserving ai system and applied ethics. In: 2022 IEEE 16th International Conference on Semantic Computing (ICSC), pp. 9–16 (2022). https://doi.org/10.1109/ICSC52841.2022.00010

  23. Sirichotedumrong, W., Kiya, H.: A GAN-based image transformation scheme for privacy-preserving deep neural networks. In: 2020 28th European Signal Processing Conference (EUSIPCO), pp. 745–749 (2021). https://doi.org/10.23919/Eusipco47968.2020.9287532

  24. Wu, Y., Noonan, J.P., Agaian, S., et al.: NPCR and UACI randomness tests for image encryption. Cyber J. Multi. J. Sci. Tech. J. Sel. Areas Telecommun. (JSAT) 1(2), 31–38 (2011)

    Google Scholar 

  25. Yang, G., Cao, J., Chen, Z., Guo, J., Li, J.: Graph-based neural networks for explainable image privacy inference. Pattern Recogn. 105, 107360 (2020). https://doi.org/10.1016/j.patcog.2020.107360, https://www.sciencedirect.com/science/article/pii/S0031320320301631

  26. Yang, J., Liu, J., Han, R., Wu, J.: Transferable face image privacy protection based on federated learning and ensemble models. Complex Intell. Syst. 7(5), 2299–2315 (2021). https://doi.org/10.1007/s40747-021-00399-6

    CrossRef  Google Scholar 

  27. Yoosefian Dezfuli Nezhad, S., Safdarian, N., Hoseini Zadeh, S.A.: New method for fingerprint images encryption using DNA sequence and chaotic tent map. Optik 224, 165661 (2020). https://doi.org/10.1016/j.ijleo.2020.165661, https://www.sciencedirect.com/science/article/pii/S0030402620314923

  28. Zhang, Y.: The fast image encryption algorithm based on lifting scheme and chaos. Inf. Sci. 520, 177–194 (2020). https://doi.org/10.1016/j.ins.2020.02.012, https://www.sciencedirect.com/science/article/pii/S0020025520300748

Download references

Author information

Authors and Affiliations

  1. Guangxi Key Laboratory of Trusted Software, School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China

    Zhen Liu & Yining Liu

  2. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark

    Weizhi Meng

Authors
  1. Zhen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yining Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weizhi Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yining Liu .

Editor information

Editors and Affiliations

  1. University of Malaga, Malaga, Spain

    Cristina Alcaraz

  2. University of Surrey, Guildford, UK

    Liqun Chen

  3. University of Kent, Canterbury, UK

    Shujun Li

  4. University of Milan, Milan, Italy

    Pierangela Samarati

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, Z., Liu, Y., Meng, W. (2022). Lightweight and Practical Privacy-Preserving Image Masking in Smart Community. In: Alcaraz, C., Chen, L., Li, S., Samarati, P. (eds) Information and Communications Security. ICICS 2022. Lecture Notes in Computer Science, vol 13407. Springer, Cham. https://doi.org/10.1007/978-3-031-15777-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-15777-6_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15776-9

  • Online ISBN: 978-3-031-15777-6

  • eBook Packages: Computer ScienceComputer Science (R0)

search

Navigation