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Volume 45 Issue 3
Mar.  2023
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OUYANG Xue, XU Yanyan, MAO Yangsu, LIU Yunqi, WANG Zhiheng, YAN Yuejing. Secure Remote Sensing Image Retrieval Scheme Based on Cloud Computing and Blockchain Platforms[J]. Journal of Electronics & Information Technology, 2023, 45(3): 856-864. doi: 10.11999/JEIT220956
Citation: OUYANG Xue, XU Yanyan, MAO Yangsu, LIU Yunqi, WANG Zhiheng, YAN Yuejing. Secure Remote Sensing Image Retrieval Scheme Based on Cloud Computing and Blockchain Platforms[J]. Journal of Electronics & Information Technology, 2023, 45(3): 856-864. doi: 10.11999/JEIT220956

Secure Remote Sensing Image Retrieval Scheme Based on Cloud Computing and Blockchain Platforms

doi: 10.11999/JEIT220956
Funds:  The National Key Research and Development Program of China (2021YFB2501103), The National Natural Science Foundation of China (42271431), The National Key Project of Hubei Provincial Natural Science Foundation (2020CFA001)
  • Received Date: 2022-07-18
  • Rev Recd Date: 2023-02-27
  • Available Online: 2023-02-28
  • Publish Date: 2023-03-10
  • Remote sensing image storage and retrieval outsourcing to a semi-trusted cloud platform may lead to image data leakage and return incomplete retrieval results. Although encryption can protect the security of image data, it can not ensure that the cloud platform provides accurate and complete storage and retrieval services. Blockchain technology guarantees the authenticity and integrity of storage and retrieval services, but the computation and storage capacity of blockchain are limited, which makes it a challenging problem to realize secure storage and retrieval of remote sensing images. This paper proposes a secure remote sensing image retrieval scheme based on blockchain and cloud computing platforms. To secure the validity of cloud-saved images, the image hash and lightweight data are first stored on the blockchain, while the cloud platform stores huge encrypted image data. Moreover, the blockchain performs attribute-based retrieval of remote sensing images, and the cloud platform performs content-based secure retrieval to ensure the integrity of the retrieval results. Finally, the remote sensing image retrieval transaction mechanism is designed using blockchain technology. The experiments show that the proposed scheme can achieve secure, reliable, and fair remote sensing image retrieval, enabling both trading sides to benefit from a high-trust and fair-trading environment.
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  • [1]
    徐彦彦, 赵啸, 李子君. 一种基于四元数变换的彩色遥感影像检索方法[J]. 武汉大学学报:信息科学版, 2019, 44(11): 1633–1640. doi: 10.13203/j.whugis20170290

    XU Yanyan, ZHAO Xiao, and LI Zijun. A remote sensing image retrieval method based on quaternion transformation[J]. Geomatics and Information Science of Wuhan University, 2019, 44(11): 1633–1640. doi: 10.13203/j.whugis20170290
    [2]
    SHEN Meng, CHENG Guohua, ZHU Liehuang, et al. Content-based multi-source encrypted image retrieval in clouds with privacy preservation[J]. Future Generation Computer Systems, 2020, 109: 621–632. doi: 10.1016/j.future.2018.04.089
    [3]
    鲁金钿, 肖睿智, 金舒原. 云数据安全研究进展[J]. 电子与信息学报, 2021, 43(4): 881–891. doi: 10.11999/JEIT200158

    LU Jintian, XIAO Ruizhi, and JIN Shuyuan. A survey for cloud data security[J]. Journal of Electronics &Information Technology, 2021, 43(4): 881–891. doi: 10.11999/JEIT200158
    [4]
    HUANG Wei, GANJALI A, KIM B H, et al. The state of public infrastructure-as-a-service cloud security[J]. ACM Computing Surveys, 2015, 47(4): 68. doi: 10.1145/2767181
    [5]
    NAKAMOTO S. Bitcoin: A peer-to-peer electronic cash system[J/OL]. Decentralized Business Review, 2008: 21260.
    [6]
    陈杰, 戴欣宜, 周兴, 等. 双LSTM驱动的高分遥感影像地物目标空间关系语义描述[J]. 遥感学报, 2021, 25(5): 1085–1094. doi: 10.11834/jrs.20210340

    CHEN Jie, DAI Xinyi, ZHOU Xing, et al. Semantic understanding of geo-objects’ relationship in high resolution remote sensing image driven by dual LSTM[J]. National Remote Sensing Bulletin, 2021, 25(5): 1085–1094. doi: 10.11834/jrs.20210340
    [7]
    LI Yansheng, MA Jiayi, and ZHANG Yongjun. Image retrieval from remote sensing big data: A survey[J]. Information Fusion, 2021, 67: 94–115. doi: 10.1016/j.inffus.2020.10.008
    [8]
    WATERS B. Ciphertext-policy attribute-based encryption: An expressive, efficient, and provably secure realization[C]. Proceedings of the 14th International Workshop on Public Key Cryptography, Taormina, Italy, 2011: 53–70.
    [9]
    ZHANG Yan, ZHUO Li, PENG Yuanfan, et al. A secure image retrieval method based on homomorphic encryption for cloud computing[C]. The 19th International Conference on Digital Signal Processing, Hong Kong, China, 2014: 269–274.
    [10]
    LU Wenjun, VARNA A L, SWAMINATHAN A, et al. Secure image retrieval through feature protection[C]. 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, China, 2009: 1533–1536.
    [11]
    徐彦彦, 张逸然, 闫悦菁, 等. 云环境下基于秘密共享的图像安全检索方案[J]. 华中科技大学学报:自然科学版, 2021, 49(6): 31–36. doi: 10.13245/j.hust.210606

    XU Yanyan, ZHANG Yiran, YAN Yuejing, et al. Privacy-preserving image retrieval scheme based on secret sharing in cloud environment[J]. Journal of Huazhong University of Science and Technology:Natural Science Edition, 2021, 49(6): 31–36. doi: 10.13245/j.hust.210606
    [12]
    LI Huige, TIAN Haibo, ZHANG Fangguo, et al. Blockchain-based searchable symmetric encryption scheme[J]. Computers & Electrical Engineering, 2019, 73: 32–45. doi: 10.1016/j.compeleceng.2018.10.015
    [13]
    ZHANG Yuan, XU Chunxiang, NI Jianbing, et al. Blockchain-assisted public-key encryption with keyword search against keyword guessing attacks for cloud storage[J]. IEEE Transactions on Cloud Computing, 2021, 9(4): 1335–1348. doi: 10.1109/TCC.2019.2923222
    [14]
    WANG Shangping, ZHANG Yinglong, and ZHANG Yaling. A blockchain-based framework for data sharing with fine-grained access control in decentralized storage systems[J]. IEEE Access, 2018, 6: 38437–38450. doi: 10.1109/ACCESS.2018.2851611
    [15]
    DOLEV D and YAO A. On the security of public key protocols[J]. IEEE Transactions on Information Theory, 1983, 29(2): 198–208. doi: 10.1109/TIT.1983.1056650
    [16]
    HE Kaiming, ZHANG Xiangyu, REN Shaoqing, et al. Deep residual learning for image recognition[C]. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, 2016: 770–778.
    [17]
    GALLAS J A C. Structure of the parameter space of the hénon map[J]. Physical Review Letters, 1993, 70(18): 2714–2717. doi: 10.1103/PhysRevLett.70.2714
    [18]
    BRAKERSKI Z, GENTRY C, and HALEVI S. Packed ciphertexts in lwe-based homomorphic encryption[C]. Proceedings of the 16th International Workshop on Public Key Cryptography, Nara, Japan, 2013: 1–13.
    [19]
    SHAO Zhenfeng, ZHOU Weixun, DENG Xueqing, et al. Multilabel remote sensing image retrieval based on fully convolutional network[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 318–328. doi: 10.1109/JSTARS.2019.2961634
    [20]
    CHAUDHURI B, DEMIR B, CHAUDHURI S, et al. Multilabel remote sensing image retrieval using a semisupervised graph-theoretic method[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(2): 1144–1158. doi: 10.1109/TGRS.2017.2760909
    [21]
    LI Weng, AMSALEG L, MORTON A, et al. A Privacy-preserving framework for large-scale content-based information retrieval[J]. IEEE Transactions on Information Forensics and Security, 2015, 10(1): 152–167. doi: 10.1109/TIFS.2014.2365998
    [22]
    XIA Zhihua, JIANG Leqi, LIU Dandan, et al. BOEW: A content-based image retrieval scheme using bag-of-encrypted-words in cloud computing[J]. IEEE Transactions on Services Computing, 2022, 15(1): 202–214. doi: 10.1109/TSC.2019.2927215
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