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A Format-compatible Searchable Encryption Scheme for JPEG Images Using Bag-of-words

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Published:15 March 2022Publication History
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Abstract

The development of cloud computing attracts enterprises and individuals to outsource their data, such as images, to the cloud server. However, direct outsourcing causes the extensive concern of privacy leakage, as images often contain rich sensitive information. A straightforward way to protect privacy is to encrypt the images using the standard cryptographic tools before outsourcing. However, in such a way the possible usage of the outsourced images would be strongly limited together with the services provided to users, like the Content-Based Image Retrieval (CBIR). In this article, we propose a secure outsourced CBIR scheme, in which an encryption scheme is designed for the widely used JPEG-format images, and the secure features can be directly extracted from such encrypted images. Specifically, the JPEG images are encrypted by the block permutation, intra-block permutation, polyalphabetic cipher, and stream cipher. Then secure local histograms are extracted from the encrypted DCT blocks and the Bag-Of-Words (BOW) model is further used to organize the encrypted local features to represent the image. The proposed image encryption gets all of the image data protected and the experimental results show that the proposed scheme achieves improved accuracy with a small file size expansion.

REFERENCES

  1. [1] Awasthi Prakhar, Mittal Sanya, Mukherjee Sibeli, and Limbasiya Trupil. 2019. A protected cloud computation algorithm using homomorphic encryption for preserving data integrity. In Recent Findings in Intelligent Computing Techniques. Springer, 509517.Google ScholarGoogle ScholarCross RefCross Ref
  2. [2] Bellafqira Reda, Coatrieux Gouenou, Bouslimi Dalel, and Quellec Gwénolé. 2015. Content-based image retrieval in homomorphic encryption domain. In 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 29442947.Google ScholarGoogle ScholarCross RefCross Ref
  3. [3] Benhamouda Fabrice, Halevi Shai, and Halevi Tzipora. 2019. Supporting private data on hyperledger fabric with secure multiparty computation. IBM J. Res. Devel. 63, 2/3 (2019), 3–1.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. [4] Cheng Hang, Zhang Xinpeng, Yu Jiang, and Li Fengyong. 2016. Markov process-based retrieval for encrypted JPEG images. EURASIP J. Inf. Secur. 2016, 1 (2016), 1.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. [5] Cheng Hang, Zhang Xinpeng, Yu Jiang, and Zhang Yuan. 2016. Encrypted JPEG image retrieval using block-wise feature comparison. J. Vis. Commun. Image Repres. 40 (2016), 111117.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. [6] Cheng Shu-Li, Wang Lie-Jun, Huang Gao, and Du An-Yu. 2021. A privacy-preserving image retrieval scheme based secure kNN, DNA coding and deep hashing. Multim. Tools Applic. 80, 15 (2021), 2273322755.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. [7] Chum Ondrej, Philbin James, Zisserman Andrew et al. 2008. Near duplicate image detection: Min-hash and TF-IDF weighting. In British Machine Vision Conference, Vol. 810. 812815.Google ScholarGoogle ScholarCross RefCross Ref
  8. [8] Ferreira Bernardo, Rodrigues Joao, Leitao Joao, and Domingos Henrique. 2017. Practical privacy-preserving content-based retrieval in cloud image repositories. IEEE Trans. Cloud Comput. 7, 3 (2017), 784–798.Google ScholarGoogle Scholar
  9. [9] Gu Qi, Xia Zhihua, and Sun Xingming. 2020. MSPPIR: Multi-source privacy-preserving image retrieval in cloud computing. arXiv preprint arXiv:2007.12416.Google ScholarGoogle Scholar
  10. [10] Guo Cheng, Jia Jing, Choo Kim-Kwang Raymond, and Jie Yingmo. 2020. Privacy-preserving image search (PPIS): Secure classification and searching using convolutional neural network over large-scale encrypted medical images. Comput. Secur. 99 (2020), 102021.Google ScholarGoogle ScholarCross RefCross Ref
  11. [11] Hsu Chao-Yung, Lu Chun-Shien, and Pei Soo-Chang. 2012. Image feature extraction in encrypted domain with privacy-preserving SIFT. IEEE Trans. Image Process. 21, 11 (2012), 45934607.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. [12] Hu Lishuang, Xiang Tao, and Guo Shangwei. 2020. SensIR: Towards privacy-sensitive image retrieval in the cloud. Sig. Process.: Image Commun. 84 (2020), 115837.Google ScholarGoogle ScholarCross RefCross Ref
  13. [13] Hu Shengshan, Wang Qian, Wang Jingjun, Qin Zhan, and Ren Kui. 2016. Securing SIFT: Privacy-preserving outsourcing computation of feature extractions over encrypted image data. IEEE Trans. Image Process. 25, 7 (2016), 34113425.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. [14] Iakovidou Chryssanthi, Anagnostopoulos Nektarios, Lux Mathias, Christodoulou Klitos, Boutalis Y., and Chatzichristofis Savvas A.. 2019. Composite description based on salient contours and color information for CBIR tasks. IEEE Trans. Image Process. 28, 6 (2019), 31153129.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. [15] Iida Kenta and Kiya Hitoshi. 2020. Privacy-preserving content-based image retrieval using compressible encrypted images. IEEE Access 8 (2020), 200038200050.Google ScholarGoogle ScholarCross RefCross Ref
  16. [16] Iida Kenta and Kiya Hitoshi. 2021. A content-based image retrieval scheme using compressible encrypted images. In 28th European Signal Processing Conference (EUSIPCO). IEEE, 730734.Google ScholarGoogle ScholarCross RefCross Ref
  17. [17] Janani T. and Brindha M.. 2021. SEcure similar image matching (SESIM): An improved privacy preserving image retrieval protocol over encrypted cloud database. IEEE Trans. Multim.DOI:Google ScholarGoogle ScholarCross RefCross Ref
  18. [18] Li Bin, Ding Shilei, and Yang Xu. 2021. A privacy-preserving scheme for JPEG image retrieval based on deep learning. In Journal of Physics: Conference Series, Vol. 1856. IOP Publishing, 012007.Google ScholarGoogle ScholarCross RefCross Ref
  19. [19] Li Jia and Wang James Ze. 2003. Automatic linguistic indexing of pictures by a statistical modeling approach. IEEE Trans. Pattern Anal. Mach. Intell. 25, 9 (2003), 10751088.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. [20] Li Yingying, Ma Jianfeng, Miao Yinbin, Wang Yue, Yang Tengfei, Liu Ximeng, and Choo Kim-Kwang Raymond. 2020. Traceable and controllable encrypted cloud image search in multi-user settings. IEEE Trans. Cloud Comput.DOI:Google ScholarGoogle ScholarCross RefCross Ref
  21. [21] Liang Haihua, Zhang Xinpeng, and Cheng Hang. 2019. Huffman-code based retrieval for encrypted JPEG images. J. Vis. Commun. Image Repres. 61 (2019), 149156.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. [22] Liu Fei, Wang Yong, Wang Fan-Chuan, Zhang Yong-Zheng, and Lin Jie. 2019. Intelligent and secure content-based image retrieval for mobile users. IEEE Access 7 (2019), 119209119222.Google ScholarGoogle ScholarCross RefCross Ref
  23. [23] Lu Wenjun, Swaminathan Ashwin, Varna Avinash L., and Wu Min. 2009. Enabling search over encrypted multimedia databases. In Media Forensics and Security, Vol. 7254. International Society for Optics and Photonics, 725418.Google ScholarGoogle Scholar
  24. [24] Lu Wenjun, Varna Avinash L., Swaminathan Ashwin, and Wu Min. 2009. Secure image retrieval through feature protection. In IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 15331536.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. [25] Shen Meng, Cheng Guohua, Zhu Liehuang, Du Xiaojiang, and Hu Jiankun. 2020. Content-based multi-source encrypted image retrieval in clouds with privacy preservation. Fut. Gen. Comput. Syst. 109 (2020), 621632.Google ScholarGoogle ScholarCross RefCross Ref
  26. [26] Sivic Josef and Zisserman Andrew. 2003. Video Google: A text retrieval approach to object matching in videos. In IEEE International Conference on Computer Vision, vol. 3. IEEE Computer Society, 1470–1470.Google ScholarGoogle Scholar
  27. [27] Wang James Ze, Li Jia, and Wiederhold Gio. 2001. SIMPLIcity: Semantics-sensitive integrated matching for picture libraries. IEEE Trans. Pattern Anal. Mach. Intell. 23, 9 (2001), 947963.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. [28] Wang Zhangdong, Qin Jiaohua, Xiang Xuyu, and Tan Yun. 2021. A privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing. Multim. Syst. 27 (2021), 113.Google ScholarGoogle Scholar
  29. [29] Weng Li, Amsaleg Laurent, and Furon Teddy. 2016. Privacy-preserving outsourced media search. IEEE Trans. Knowl. Data Eng. 28, 10 (2016), 27382751.Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. [30] Weng Li, Amsaleg Laurent, Morton April, and Marchand-Maillet Stéphane. 2014. A privacy-preserving framework for large-scale content-based information retrieval. IEEE Trans. Inf. Forens. Secur. 10, 1 (2014), 152167.Google ScholarGoogle ScholarCross RefCross Ref
  31. [31] Xia Zhihua, Jiang Leqi, Liu Dandan, Lu Lihua, and Jeon Byeungwoo. 2019. BOEW: A content-based image retrieval scheme using bag-of-encrypted-words in cloud computing. IEEE Trans. Serv. Comput.DOI:Google ScholarGoogle ScholarCross RefCross Ref
  32. [32] Xia Zhihua, Wang Xinhui, Zhang Liangao, Qin Zhan, Sun Xingming, and Ren Kui. 2016. A privacy-preserving and copy-deterrence content-based image retrieval scheme in cloud computing. IEEE Trans. Inf. Forens. Secur. 11, 11 (2016), 25942608.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. [33] Xia Zhihua, Zhu Yi, Sun Xingming, Qin Zhan, and Ren Kui. 2015. Towards privacy-preserving content-based image retrieval in cloud computing. IEEE Trans. Cloud Comput. 6, 1 (2015), 276286.Google ScholarGoogle ScholarCross RefCross Ref
  34. [34] Xu Yanyan, Gong Jiaying, Xiong Lizhi, Xu Zhengquan, Wang Jinwei, and Shi Yun-qing. 2017. A privacy-preserving content-based image retrieval method in cloud environment. J. Vis. Commun. Image Repres. 43 (2017), 164172.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. [35] Yuan Jiawei, Yu Shucheng, and Guo Linke. 2015. SEISA: Secure and efficient encrypted image search with access control. In IEEE Conference on Computer Communications (INFOCOM). IEEE, 20832091.Google ScholarGoogle ScholarCross RefCross Ref
  36. [36] Zhang Chengyuan, Zhu Lei, Zhang Shichao, and Yu Weiren. 2020. TDHPPIR: An efficient deep hashing based privacy-preserving image retrieval method. Neurocomputing 406 (2020), 386398.Google ScholarGoogle ScholarCross RefCross Ref
  37. [37] Zhang Lan, Jung Taeho, Liu Kebin, Li Xiang-Yang, Ding Xuan, Gu Jiaxi, and Liu Yunhao. 2017. PIC: Enable large-scale privacy preserving content-based image search on cloud. IEEE Trans. Parallel Distrib. Syst. 28, 11 (2017), 32583271.Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Transactions on Multimedia Computing, Communications, and Applications
      ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 18, Issue 3
      August 2022
      478 pages
      ISSN:1551-6857
      EISSN:1551-6865
      DOI:10.1145/3505208
      Issue’s Table of Contents

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      • Published: 15 March 2022
      • Accepted: 1 October 2021
      • Revised: 1 September 2021
      • Received: 1 April 2020
      Published in tomm Volume 18, Issue 3

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