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Tsinghua Science and Technology 2023, 28(5): 849-861 https://doi.org/10.26599/TST.2022.9010066
Open Access | Issue | Published: 19 May 2023

A Copyright-Preserving and Fair Image Trading Scheme Based on Blockchain

Show Author's Information Feng Yu1( ),  Jiahui Peng2( ),  Xianxian Li1,  Chunpei Li1,  Bin Qu1
School of Computer Science & Engineering, Guangxi Normal University, Guilin 541004, China, and with the Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China, and also with Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing, Guangxi Normal University, Guilin 541004, China
Guangxi Power Grid Materials Co Ltd, Nanning 530022, China
Keywords:
blockchain, copyright-preserving trade, fair trade, tadors code
Cite this article:
Yu F, Peng J, Li X, et al. A Copyright-Preserving and Fair Image Trading Scheme Based on Blockchain. Tsinghua Science and Technology, 2023, 28(5): 849-861. https://doi.org/10.26599/TST.2022.9010066
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Abstract Full text About this article

With the proliferation of the Internet, particularly the rise of social media, digital images have gradually become an important part of life, and trading platforms have emerged for buying and selling images. However, traditional image trading service providers may disclose users’ private information for profit. Additionally, many image trading platforms disregard the fairness of a transaction and the issue of copyright protection after an image is sold. This neglect harms the interests of users and affects their enthusiasm for trading. A secure way to safely transact images is needed. We proposed a copyright-preserving and fair image trading scheme based on blockchain, which combines amplifying locality-sensitive hashing with searchable symmetric encryption to achieve safe image retrieval on blockchain and ensure the credibility of the image retrieval process. Additionally, we use digital fingerprint and watermark technologies to realize the copyright protection of images and use smart contracts to achieve fair transaction processes. The experimental results show that our scheme can protect image copyrights and realize a fair trading process while ensuring efficiency.


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About this article

A Copyright-Preserving and Fair Image Trading Scheme Based on Blockchain

Show Author's information Feng Yu1( ), Jiahui Peng2( ), Xianxian Li1, Chunpei Li1, Bin Qu1
School of Computer Science & Engineering, Guangxi Normal University, Guilin 541004, China, and with the Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China, and also with Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing, Guangxi Normal University, Guilin 541004, China
Guangxi Power Grid Materials Co Ltd, Nanning 530022, China

Abstract

With the proliferation of the Internet, particularly the rise of social media, digital images have gradually become an important part of life, and trading platforms have emerged for buying and selling images. However, traditional image trading service providers may disclose users’ private information for profit. Additionally, many image trading platforms disregard the fairness of a transaction and the issue of copyright protection after an image is sold. This neglect harms the interests of users and affects their enthusiasm for trading. A secure way to safely transact images is needed. We proposed a copyright-preserving and fair image trading scheme based on blockchain, which combines amplifying locality-sensitive hashing with searchable symmetric encryption to achieve safe image retrieval on blockchain and ensure the credibility of the image retrieval process. Additionally, we use digital fingerprint and watermark technologies to realize the copyright protection of images and use smart contracts to achieve fair transaction processes. The experimental results show that our scheme can protect image copyrights and realize a fair trading process while ensuring efficiency.

Keywords: blockchain, copyright-preserving trade, fair trade, tadors code

References(36)

[1]
O. B. Sezer and A. M. Ozbayoglu, Financial trading model with stock bar chart image time series with deep convolutional neural networks, arXiv preprint arXiv:1903.04610, 2019.
DOI Google Scholar
[2]
N. Cohen, T. Balch, and M. Veloso, Trading via image classification, in Proceedings of the First ACM International Conference on AI in Finance ACM, New York, NY, USA, 2020. pp. 1–6.
DOI Google Scholar
[3]
W. Sae-Tang, M. Fujiyoshi, and H. Kiya, A new copyright-and privacy-protected image trading system using a novel steganographybased visual encryption scheme, ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 17, no. 1, pp. 95–107, 2019.
DOI Google Scholar
[4]
W. Sae-Tang and H. Kiya, Hadamard transform-based amplitude-only images for image trading systems, in Proc. of International Workshop on Advanced Image Technology, Busan, Republic of Korea, 2016, pp. 1–4.
Google Scholar
[5]
Z. Ma, Digital rights management: Model, technology and application, China Communications, vol. 14, no. 6, pp. 156–167, 2017.
DOI Google Scholar
[6]
T. Chen, T. C. Chang, and T. Zhu, Security-enhanced cloud-based image secret sharing and authentication using POB number system, Multimed. Tools Appl., vol. 80, no. 2, pp. 1901–1924, 2021.
DOI Google Scholar
[7]
Z. Wu, H. Li, X. Wang, Z. Wu, L. Zou, L. Xu, and M. Tan, New benchmark for household garbage image recognition, Tsinghua Science and Technology, vol. 27, no. 5, pp. 793–803, 2022.
DOI Google Scholar
[8]
L. Wang, X. Liu, and X. Lin, A fair and privacy-preserving image trading system based on blockchain and group signature, Secur. Commun. Netw., vol. 2021, p. 5701258, 2021.
DOI Google Scholar
[9]
J. Song, E. Kang, H. W. Shin, and J. Jang, A smart contract-based P2P energy trading system with dynamic pricing on ethereum blockchain, Sensors, vol. 21, no. 6, pp. 1985, 2021.
DOI Google Scholar
[10]
T. Li, H. Wang, and D. He, Blockchain-based privacypreserving and rewarding private data sharing for IoT, IEEE Internet of Things Journal, vol. 9, no. 16, pp. 15138–15149, 2022.
DOI Google Scholar
[11]
J. Shen, Blockchain technology and its applications in digital content copyright protection, in Proc. 4th Int. Conf. Economic Management and Green Development, Singapore, 2021, pp. 18–25.
DOI Google Scholar
[12]
S. Nakamoto. Bitcoin: A peer-to-peer electronic cash system, Decentralized Business Review, vol. 21, no. 5, pp. 21260–21268, 2008.
Google Scholar
[13]
G. B. Mermer, E. Zeydan, and S. S. Arslan, An overview of blockchain technologies: Principles, opportunities and challenges, in Proc. 2018 26th Signal Processing and Communications Applications Conf. (SIU), Izmir, Turkey, 2018, pp. 1–4.
DOI Google Scholar
[14]
J. Ren, J. Li, H. Liu, and T. Qin, Task offloading strategy with emergency handling and blockchain security in SDN-empowered and fog-assisted healthcare IoT, Tsinghua Science and Technology, vol. 27, no. 4, pp. 760–776, 2022.
DOI Google Scholar
[15]
H. Ma, H. Ding, Y. Yang, Z. Mi, J. Y. Yang, and Z. Xiong, Bayes-based arp attack detection algorithm for cloud centers, Tsinghua Science and Technology, vol. 21, no. 1, pp. 17–28, 2016.
DOI Google Scholar
[16]
X. Li, J. Li, F. Yu, J. Yang, and Y. Chen, BEIR: A blockchain-based encrypted image retrieval scheme, in Proc. 2021 IEEE 24th Int. Conf. Computer Supported Cooperative Work in Design (CSCWD), Dalian, China, 2021, pp. 452–457.
DOI Google Scholar
[17]
M. Shen, Y. Deng, L. Zhu, X. Du, and N. Guizani, Privacy-preserving image retrieval for medical IoT systems: A blockchain-based approach, IEEE Netw., vol. 33, no. 5, pp. 27–33, 2019.
DOI Google Scholar
[18]
M. Li, M. Zhang, Q. Wang, S. S. M. Chow, M. Du, Y. Chen, and C. Lit, InstantCryptoGram: Secure image retrieval service, in Proc. IEEE INFOCOM 2018 - IEEE Conf. Computer Communications, Honolulu, HI, USA, 2018, pp. 2222–2230.
DOI Google Scholar
[19]
S. Hu, C. Cai, Q. Wang, C. Wang, Z. Wang, and D. Ye, Augmenting encrypted search: A decentralized service realization with enforced execution, IEEE Trans. Depend. Secure Comput., vol. 18, no. 6, pp. 2569–2581, 2019.
DOI Google Scholar
[20]
A. Savelyev, Copyright in the blockchain era: Promises and challenges, Comput. Law Secur. Rev., vol. 34, no. 3, pp. 550–561, 2018.
DOI Google Scholar
[21]
S. Tulyakov, F. Farooq, and V. Govindaraju, Symmetric hash functions for fingerprint minutiae, in Proc. Third Int. Conf. Pattern Recognition and Image Analysis, Bath, UK, 2005, pp. 30–38.
DOI Google Scholar
[22]
A. Charpentier, C. Fontaine, T. Furon, and I. Cox, An asymmetric fingerprinting scheme based on Tardos codes, in Proc. 13th Int. Workshop on Information Hiding, Prague, Czech Republic, 2011, pp. 43–58.
DOI Google Scholar
[23]
F. Farooq, R. M. Bolle, T. Y. Jea, and N. Ratha, Anonymous and revocable fingerprint recognition, in Proc. 2007 IEEE Conf. on Computer Vision and Pattern Recognition, Minneapolis, MN, USA, 2007, pp. 1–7.
DOI Google Scholar
[24]
Q. Liu, R. Safavi-Naini, and N. P. Sheppard, Digital rights management for content distribution, in Proc. Australasian Information Security Workshop Conf. ACSW Frontiers 2003, Adelaide, Australia, 2003, pp. 49–58.
Google Scholar
[25]
Z. Ma, M. Jiang, H. Gao, and Z. Wang, Blockchain for digital rights management, Fut. Generat. Comput. Syst., vol. 89, pp. 746–764, 2018.
DOI Google Scholar
[26]
S. Kenny and L. Korba, Applying digital rights management systems to privacy rights management, Comput. Secur., vol. 21, no. 7, pp. 648–664, 2002.
DOI Google Scholar
[27]
C. Huang, D. Liu, J. Ni, R. Lu, and X. Shen, Achieving accountable and efficient data sharing in industrial internet of things, IEEE Trans. Ind. Inf., vol. 17, no. 2, pp. 1416–1427, 2021.
DOI Google Scholar
[28]
Z. Chen, Y. Wang, and T. Ni, DCDChain: A credible architecture of digital copyright detection based on blockchain, arXiv preprint arXiv: 2010.01235v2, 2020.
Google Scholar
[29]
D. Sheng, M. Xiao, A. Liu, X. Zou, B. An, and S. Zhang, CPchain: A copyright-preserving crowdsourcing data trading framework based on blockchain, in Proc. 2020 29th International Conference on Computer Communications and Networks (ICCCN), Honolulu, HI, USA, 2020, pp. 1–9.
DOI Google Scholar
[30]
Y. Wei and C. Jin, Locality sensitive discriminant projection for feature extraction and face recognition, J. Electr. Imag., vol. 28, no. 4, p. 043028, 2019.
DOI Google Scholar
[31]
Q. Wang, X. Zhang, J. Qin, J. Ma, and X. Huang, A verifiable symmetric searchable encryption scheme based on the AVL tree, Comput. J., vol. 66, no. 1, pp. 174–183, 2023.
DOI Google Scholar
[32]
M. A. Saviour and D. Samiappan, IPFS based file storage access control and authentication model for secure data transfer using block chain technique, Concurr. Comput. Pract. Exp., vol. 35, no. 2, p. e7485, 2023.
DOI Google Scholar
[33]
A. Rubinstein, Perfect equilibrium in a bargaining model, Econometrica, vol. 50, no. 1, pp. 97–109, 1982.
DOI Google Scholar
[34]
F. Radenović, G. Tolias, and O. Chum, CNN image retrieval learns from BoW: Unsupervised fine-tuning with hard examples, in Proc. 14th European Conf. Computer Vision, Amsterdam, the Netherlands, 2016, pp. 3–20.
DOI Google Scholar
[35]
N. Ren, D. Tong, H. Cui, C. Zhu, and Q. Zhou, Congruence and geometric feature-based commutative encryption-watermarking method for vector maps, Comput. Geosci., vol. 159, p. 105009, 2022.
DOI Google Scholar
[36]
B. Škorić and J. J. Oosterwijk, Binary and q-ary Tardos codes, revisited, Des. Codes Cryptogr., vol. 74, no. 1, pp. 75–111, 2015.
DOI Google Scholar
Publication history
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Publication history

Received: 06 December 2022
Accepted: 20 December 2022
Published: 19 May 2023
Issue date: October 2023

Copyright

© The author(s) 2023.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 62062016 and U21A20474), Guangxi Natural Science Foundation (No. 2019JJA170060), Jiangsu Provincial Key Laboratory of Network and Information Security (No. BM2003201), and Guangxi Science and Technology project (Nos. GuikeAA22067070 and GuikeAD21220114). Finally, we thank the Guangxi "Bagui Scholar" Teams for Innovation and Research Project, Center for Applied Mathematics of Guangxi (Guangxi Normal University), and the Guangxi Talent Highland Project of Big Data Intelligence and Application.

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