RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain

Liang WANG; Shunjiu HUANG; Lina ZUO; Jun LI; Wenyuan LIU

doi:10.1631/FITEE.2200659

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RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain

Regular Papers | Updated：2023-08-29

- RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain
  Enhanced Publication
- RCDS：一种基于符号映射编码和区块链的可确权数据共享模型
- Frontiers of Information Technology & Electronic Engineering Vol. 24, Issue 8, Pages: 1194-1213(2023)
- Affiliations：
  
  1.School of Cyber Security and Computer, Hebei University, Baoding 071000, China
  2.Xiong’an Intelligent City Innovation Federation, Xiong'an 071700, China
  3.School of Information Science and Engineering, Yanshan University, Qinhuangdao 066000, China
- Author bio：
  
  †E-mail: wangl@hbu.edu.cn
  ‡Corresponding author
- Funds：
- DOI：10.1631/FITEE.2200659
  CLC： TP309.2
- Published：0 August 2023，
  
  Received：24 December 2022，
  
  Accepted：2023-03-27
- Accepted：
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LIANG WANG, SHUNJIU HUANG, LINA ZUO, et al. RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain. [J]. Frontiers of information technology & electronic engineering, 2023, 24(8): 1194-1213.
DOI：

LIANG WANG, SHUNJIU HUANG, LINA ZUO, et al. RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain. [J]. Frontiers of information technology & electronic engineering, 2023, 24(8): 1194-1213. DOI： 10.1631/FITEE.2200659.

摘要

数据确权问题是数据共享中长期存在的瓶颈。现有数据确权方法由于缺乏有效监管手段可信度低，且由于技术限制只能用于特定数据类型。随着区块链的出现，一些新的数据共享模型有望提供更可靠的数据安全性。然而，因为数据访问不能完全处于区块链设施的控制下，这些模型在数据确权方面的能力不足。提出一种名为RCDS以符号映射编码（SMC）和区块链为特征的可确权数据共享模型。通过SMC，数据共享各方通过生成符号映射表将其数字身份嵌入被共享数据字节序列中，从而使数据权利的声明与数据类型和数据量无关。通过区块链，所有数据共享方共同监督数据的交付和访问，从而可公开验证数据权利的授予。评价结果表明，RCDS在强调确权要求的数据共享应用中是有效且实用的。

Abstract

The problem of data right confirmation is a long-term bottleneck in data sharing. Existing methods for confirming data rights lack credibility owing to poor supervision

and work only with specific data types because of their technical limitations. The emergence of blockchain is followed by some new data-sharing models that may provide improved data security. However

few of these models perform well enough in confirming data rights because the data access could not be fully under the control of the blockchain facility. In view of this

we propose a right-confirmable data-sharing model named RCDS that features symbol mapping coding (SMC) and blockchain. With SMC

each party encodes its digital identity into the byte sequence of the shared data by generating a unique symbol mapping table

whereby declaration of data rights can be content-independent for any type and any volume of data. With blockchain

all data-sharing participants jointly supervise the delivery and the access to shared data

so that granting of data rights can be openly verified. The evaluation results show that RCDS is effective and practical in data-sharing applications that are conscientious about data right confirmation.

关键词

数据确权符号映射编码区块链数据共享叛徒追踪访问控制

Keywords

Data right confirmationSymbol mapping codingBlockchainData sharingTraitor tracingAccess control

references

Ali M, Reaz R, Gouda M, 2016. Two-phase nonrepudiation protocols. Proc 7th Int Conf on Computing Communication and Networking Technologies, Article 22. doi: 10.1145/2967878.2967903http://doi.org/10.1145/2967878.2967903

Barni M, Bartolini F, 2004. Data hiding for fighting piracy. IEEE Signal Process Mag, 21(2):28-39. doi: 10.1109/MSP.2004.1276109http://doi.org/10.1109/MSP.2004.1276109

Baumann N, Steffen S, Bichsel B, et al., 2020. zkay v0.2: practical data privacy for smart contracts. https://arxiv.org/abs/2009.01020https://arxiv.org/abs/2009.01020

Cao ZH, Zhao L, 2021. A design of key distribution mechanism in decentralized digital rights management based on blockchain and zero-knowledge proof. Proc 3rd Int Conf on Blockchain Technology, p.53-59. doi: 10.1145/3460537.3460556http://doi.org/10.1145/3460537.3460556

Chen F, Wang JH, Li JQ, et al., 2022. TrustBuilder: a non-repudiation scheme for IoT cloud applications. Comput Secur, 116:102664. doi: 10.1016/j.cose.2022.102664http://doi.org/10.1016/j.cose.2022.102664

Coffey T, Saidha P, 1996. Non-repudiation with mandatory proof of receipt. ACM SIGCOMM Comput Commun Rev, 26(1):6-17. doi: 10.1145/232335.232338http://doi.org/10.1145/232335.232338

Ersoy O, Genç ZA, Erkin Z, et al., 2021. Practical exchange for unique digital goods. Proc IEEE Int Conf on Decentralized Applications and Infrastructures, p.49-58. doi: 10.1109/DAPPS52256.2021.00011http://doi.org/10.1109/DAPPS52256.2021.00011

Frattolillo F, 2017. Digital copyright protection: focus on some relevant solutions. Int J Commun Netw Inform Secur, 9(2):282-293. doi: 10.17762/ijcnis.v9i2.2425http://doi.org/10.17762/ijcnis.v9i2.2425

Gai KK, Choo KKR, Zhu LH, 2018. Blockchain-enabled reengineering of cloud datacenters. IEEE Cloud Comput, 5(6):21-25. doi: 10.1109/MCC.2018.064181116http://doi.org/10.1109/MCC.2018.064181116

Ganesh SM, Pandi V, Deborah LJ, et al., 2017. Attacks on the anti-collusion data sharing scheme for dynamic groups in the cloud. Proc Int Conf on Security, Privacy and Anonymity in Computation, Communication and Storage, p.457-467. doi: 10.1007/978-3-319-72395-2_42http://doi.org/10.1007/978-3-319-72395-2_42

Giacomelli I, Madsen J, Orlandi C, 2016. ZKBoo: faster zero-knowledge for Boolean circuits. Proc 25th USENIX Conf on Security Symposium, p.1069-1083.

Gong JQ, Lin SF, Li JW, 2019. Research on personal health data provenance and right confirmation with smart contract. Proc IEEE 4 th Advanced Information Technology, Electronic and Automation Control Conf, p.1211-1216. doi: 10.1109/IAEAC47372.2019.8997930http://doi.org/10.1109/IAEAC47372.2019.8997930

Huckle S, White M, 2017. Fake news: a technological approach to proving the origins of content, using blockchains. Big Data, 5(4):356-371. doi: 10.1089/big.2017.0071http://doi.org/10.1089/big.2017.0071

Kalodner H, Goldfeder S, Chen XQ, et al., 2018. Arbitrum: scalable, private smart contracts. Proc 27th USENIX Security Symp, p.1353-1370.

Kappos G, Yousaf H, Maller M, et al., 2018. An empirical analysis of anonymity in Zcash. https://arxiv.org/abs/1805.03180https://arxiv.org/abs/1805.03180

Kosba A, Miller A, Shi E, et al., 2016. Hawk: the blockchain model of cryptography and privacy-preserving smart contracts. Proc IEEE Symp on Security and Privacy, p.839-858. doi: 10.1109/SP.2016.55http://doi.org/10.1109/SP.2016.55

Li C, Palanisamy B, Xu RH, 2019. Scalable and privacy-preserving design of on/off-chain smart contracts. Proc 35th Int Conf on Data Engineering Workshops, p.7-12. doi: 10.1109/ICDEW.2019.00-43http://doi.org/10.1109/ICDEW.2019.00-43

Lin C, Luo M, Huang XY, et al., 2022. An efficient privacy-preserving credit score system based on noninteractive zero-knowledge proof. IEEE Syst J, 16(1):1592-1601. doi: 10.1109/JSYST.2020.3045076http://doi.org/10.1109/JSYST.2020.3045076

Okonkwo IE, 2021. NFT, copyright and intellectual property commercialization. Int J Law Inform Technol, 29(4):296-304. doi: 10.1093/ijlit/eaab010http://doi.org/10.1093/ijlit/eaab010

Pan H, You XM, Liu S, et al., 2021. Pearson correlation coefficient-based pheromone refactoring mechanism for multi-colony ant colony optimization. Appl Intell, 51(2):752-774. doi: 10.1007/s10489-020-01841-xhttp://doi.org/10.1007/s10489-020-01841-x

Parno B, Howell J, Gentry C, et al., 2016. Pinocchio: nearly practical verifiable computation. Commun ACM, 59(2):103-112. doi: 10.1145/2856449http://doi.org/10.1145/2856449

Qian P, Liu ZG, Wang X, et al., 2019. Digital resource rights confirmation and infringement tracking based on smart contracts. Proc 6th Int Conf on Cloud Computing and Intelligence Systems, p.62-67. doi: 10.1109/CCIS48116.2019.9073733http://doi.org/10.1109/CCIS48116.2019.9073733

Saini A, Zhu QY, Singh N, et al., 2021. A smart-contract-based access control framework for cloud smart healthcare system. IEEE Int Things J, 8(7):5914-5925. doi: 10.1109/JIOT.2020.3032997http://doi.org/10.1109/JIOT.2020.3032997

Sifah EB, Xia Q, Xia H, et al., 2021. Selective sharing of outsourced encrypted data in cloud environments. IEEE Int Things J, 8(18):14141-14155. doi: 10.1109/JIOT.2021.3068226http://doi.org/10.1109/JIOT.2021.3068226

Steffen S, Bichsel B, Gersbach M, et al., 2019. zkay: specifying and enforcing data privacy in smart contracts. Proc ACM SIGSAC Conf on Computer and Communications Security, p.1759-1776. doi: 10.1145/3319535.3363222http://doi.org/10.1145/3319535.3363222

Sun XQ, Yu FR, Zhang P, et al., 2021. A survey on zero-knowledge proof in blockchain. IEEE Netw, 35(4):198-205. doi: 10.1109/MNET.011.2000473http://doi.org/10.1109/MNET.011.2000473

Wang HL, Tian YL, Yin X, 2018. Blockchain-based big data right confirmation scheme. Comput Sci, 45(2):15-19, 24(in Chinese). doi: 10.11896/j.issn.1002-137X.2018.02.003http://doi.org/10.11896/j.issn.1002-137X.2018.02.003

Wang L, Liu JY, Liu WY, et al., 2020. Blockchain-based diversion-point system for balancing customer flow in shopping mall. Symmetry, 12(12):1946. doi: 10.3390/sym12121946http://doi.org/10.3390/sym12121946

Wang L, Liu JY, Liu WY, 2021. Staged data delivery protocol: a blockchain-based two-stage protocol for non-repudiation data delivery. Concurr Comput Pract Exp, 33(13):e6240. doi: 10.1002/cpe.6240http://doi.org/10.1002/cpe.6240

Wang L, Li J, Zuo LN, et al., 2022. T-tracer: a blockchain-aided symbol mapping watermarking scheme for traitor tracing in non-repudiation data delivery. Proc 4th ACM Int Symp on Blockchain and Secure Critical Infrastructure, p.23-34. doi: 10.1145/3494106.3528674http://doi.org/10.1145/3494106.3528674

Wang S, Yang M, Ge TJ, et al., 2022. BBS: a blockchain big-data sharing system. Proc IEEE Int Conf on Communications, p.4205-4210. doi: 10.1109/ICC45855.2022.9838666http://doi.org/10.1109/ICC45855.2022.9838666

Wu ZD, 2009. A Multimedia Query Language and its Query Processing. PhD Thesis, Huazhong University of Science and Technology, Wuhan, China(in Chinese).

Yan Y, Wei CZ, Guo XP, et al., 2020. Confidentiality support over financial grade consortium blockchain. Proc ACM SIGMOD Int Conf on Management of Data, p.2227-2240. doi: 10.1145/3318464.3386127http://doi.org/10.1145/3318464.3386127

Zaghloul E, Zhou K, Ren J, 2020. P-MOD: secure privilege-based multilevel organizational data-sharing in cloud computing. IEEE Trans Big Data, 6(4):804-815. doi: 10.1109/TBDATA.2019.2907133http://doi.org/10.1109/TBDATA.2019.2907133

Zha C, Yin H, Yin B, 2020. Data ownership confirmation and privacy-free search for blockchain-based medical data sharing. Proc 2nd Int Conf on Blockchain and Trustworthy Systems, p.619-632. doi: 10.1007/978-981-15-9213-3_48http://doi.org/10.1007/978-981-15-9213-3_48

Zhang LY, Zheng YF, Weng J, et al., 2020. You can access but you cannot leak: defending against illegal content redistribution in encrypted cloud media center. IEEE Trans Depend Secur Comput, 17(6):1218-1231. doi: 10.1109/TDSC.2018.2864748http://doi.org/10.1109/TDSC.2018.2864748

Zhang R, Zhang L, Choo KKR, et al., 2023. Dynamic authenticated asymmetric group key agreement with sender non-repudiation and privacy for group-oriented applications. IEEE Trans Depend Secur Comput, 20(1):492-505. doi: 10.1109/TDSC.2021.3138445http://doi.org/10.1109/TDSC.2021.3138445

Zhao WB, Jiang CF, Gao HH, et al., 2021. Blockchain-enabled cyber-physical systems: a review. IEEE Int Things J, 8(6):4023-4034. doi: 10.1109/JIOT.2020.3014864http://doi.org/10.1109/JIOT.2020.3014864

Zhu LH, Wu YL, Gai KK, et al., 2019. Controllable and trustworthy blockchain-based cloud data management. Fut Gener Comput Syst, 91:527-535. doi: 10.1016/j.future.2018.09.019http://doi.org/10.1016/j.future.2018.09.019

Zhu ZM, Jiang R, 2016. A secure anti-collusion data sharing scheme for dynamic groups in the cloud. IEEE Trans Parall Distr Syst, 27(1):40-50. doi: 10.1109/TPDS.2015.2388446http://doi.org/10.1109/TPDS.2015.2388446

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