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Achieving fair and accountable data trading for educational multimedia data based on blockchain

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Abstract

Online education is popular for its flexibility and high accessibility. The transactions of educational multimedia data resources can effectively promote the development of educational informatization and solve the island situation of educational resources. However, educational resources may be facing severe illegal redistribution. And the copyright is not well protected. In most of existing transaction schemes for educational multimedia data, there is always a centralized third party, which may lead to dispute, distrust, or privacy issues. In this paper, we propose a fair and accountable trading scheme for educational multimedia data based on blockchain. We combine anti-collusion code named BIBD-ACC and asymmetric fingerprinting technology to achieve a relatively strong copyright protection. To realize a fair trading, we implement a smart contract with a reasonable pricing model. In addition, we leverage TEE to solve the privacy issues of public chain and IPFS to mitigate the storage cost of the blockchain. We implemented and evaluated the scheme in Ethereum. The results show that our scheme can achieve well copyright protection and preserve the users’ privacy. The overall overhead is reasonable.

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Acknowledgements

The work is partially supported by the National Natural Science Foundation of China (No. 61672176), the Guangxi “Bagui Scholar” Teams for Innovation and Research Project, the Guangxi Science and technology project (GuikeAA22067070 and GuikeAD21220114), the Center for Applied Mathematics of Guangxi (Guangxi Normal University), the Guangxi Talent Highland Project of Big Data Intelligence and Application, the Guangxi Science and Technology Plan Projects No. AD20159039, the Guangxi Young and Middle-aged Ability Improvement Project No. 2020KY02032, the Innovation Project of Guangxi Graduate Education (No. YCBZ2021038).

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  1. College of Computer Science, Guangxi Normal University, Guilin, 530022, China

    Xianxian Li, Jiahui Peng, Shiqi Gao, Zhenkui Shi & Chunpei Li

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  1. Xianxian Li
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  2. Jiahui Peng
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Correspondence to Shiqi Gao or Zhenkui Shi.

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Li, X., Peng, J., Gao, S. et al. Achieving fair and accountable data trading for educational multimedia data based on blockchain. Wireless Netw (2022). https://doi.org/10.1007/s11276-022-03042-5

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