Blockchain

Evaluation Method of Blockchain Privacy Protection for Full Life Cycle of Transaction Data

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  • 1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
    2. Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China;
    3. Institute of Internet Industry, Tsinghua University, Beijing 100084, China

Received date: 2021-11-14

  Online published: 2022-08-03

Abstract

This paper proposes an evaluation method of blockchain privacy protection for full life cycle of transaction data in view of the differences between blockchain and traditional information systems, analyzes blockchain privacy leakage risk and privacy protection methods from aspects of transaction data that are release, consensus, storage, and application to establish a blockchain privacy protection evaluation index system; conduct relative importance decision-making for index, and weight calculation using a dynamic index weight assignment method combining analytic hierarchy process and pairwise comparison; combine three dimensions of privacy protection strength, transaction data usability and privacy protection technical performance to calculate blockchain privacy protection related capability score. The analysis shows that the method enables a comprehensive evaluation of the level of blockchain privacy protection.

Cite this article

ZHU Xuguang, XING Chunxiao, LI Wenqing, HAO Yingting . Evaluation Method of Blockchain Privacy Protection for Full Life Cycle of Transaction Data[J]. Journal of Applied Sciences, 2022 , 40(4) : 555 -566 . DOI: 10.3969/j.issn.0255-8297.2022.04.002

References

[1] Nakamoto S.Bitcoin:a peer-to-peer electronic cash system[R/OL].(2008-10-31)[2021-10-28].https://www.debr.io/article/21260-bitcoin-a-peer-to-peer-electronic-cash-system.
[2] Buterin V.A next-generation smart contract and decentralized application platform[R/OL].2014[2021-10-28].https://ethereum.org/en/whitepaper/.
[3] Bamakan S M H, Motavali A, Bondarti A B.A survey of blockchain consensus algorithms performance evaluation criteria[J].Expert Systems with Applications, 2020, 154:113385.
[4] Dinh T T A, Wang J, Chen G, et al.Blockbench:a framework for analyzing private blockchains[C]//Proceedings of 2017 ACM International Conference on Management of Data, 2017:1085-1100.
[5] Tsai W T, Wang R, Liu S, et al.Compass:a data-driven blockchain evaluation framework[C]//2020 IEEE International Conference on Service Oriented Systems Engineering, 2020:17-30.
[6] Tang H, Shi Y, Dong P.Public blockchain evaluation using entropy and TOPSIS[J].Expert Systems with Applications, 2019, 117:204-210.
[7] 冷益.基于GRA-TOPSIS的区块链众筹项目评价研究[D].北京:中国石油大学, 2019.
[8] Firoozjaei M D, Lu R, Ghorbani A A.An evaluation framework for privacy-preserving solutions applicable for blockchain-based Internet-of-things platforms[J].Security and Privacy, 2020, 3(6):131.
[9] Junejo A Z, Hashmani M A, Memon M M.Empirical evaluation of privacy efficiency in blockchain networks:review and open challenges[J].Applied Sciences, 2021, 11(15):7013.
[10] 朱岩,张艺,王迪,等.网络安全等级保护下的区块链评估方法[J].工程科学学报, 2020, 42(10):1267-1285.Zhu Y, Zhang Y, Wang D, et al.Blockchain assessment methods under cybersecurity level protection[J].Journal of Engineering Science, 2020, 42(10):1267-1285.(in Chinese)
[11] 周水庚,李丰,陶宇飞,等.面向数据库应用的隐私保护研究综述[J].计算机学报, 2009, 32(5):847-861.Zhou S G, Li F, Tao Y F, et al.A Review of privacy protection research for database applications[J].Chinese Journal of Computers, 2009, 32(5):847-861.(in Chinese)
[12] 祝烈煌,高峰,沈蒙,等.区块链隐私保护研究综述[J].计算机研究与发展, 2017, 54(10):2170-2186.Zhu L H, Gao F, Shen M, et al.Survey on privacy preserving techniques for blockchain technology[J].Journal of Computer Research and Development, 2017, 54(10):2170-2186.(in Chinese)
[13] 袁勇,倪晓春,曾帅,等.区块链共识算法的发展现状与展望[J].自动化学报, 2018, 44(11):2011-2022.Yuan Y, Ni X C, Zeng S, et al.Current status and outlook of blockchain consensus algorithm development[J].Journal of Automation, 2018, 44(11):2011-2022.(in Chinese)
[14] Sweeney L.K-anonymity:a model for protecting privacy[J].International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2002, 10(5):557-570.
[15] Machanavajjhala A, Kifer D, Gehrke J, et al.l-diversity:privacy beyond k-anonymity[J].ACM Transactions on Knowledge Discovery from Data, 2007, 1(1):3-5.
[16] Li N, Li T, Venkatasubramanian S.T-closeness:privacy beyond k-anonymity and l-diversity[C]//2007 IEEE 23rd International Conference on Data Engineering, 2007:106-115, DOI:10.1109/ICDE.2007.367856.
[17] Dwork C, Roth A.The algorithmic foundations of differential privacy[J].Foundations and Trends in Theoretical Computer Science, 2014, 9(3/4):211-407.
[18] Yaji S, Bangera K, Neelima B.Privacy preserving in blockchain based on partial homomorphic encryption system for AI applications[C]//2018 IEEE 25th International Conference on High Performance Computing Workshops, 2018:81-85.DOI:10.1109/HiPCW.2018.8634280.
[19] Yan X, Wu Q, Sun Y.A homomorphic encryption and privacy protection method based on blockchain and edge computing[J].Wireless Communications and Mobile Computing, 2020:9-11.
[20] Bonneau J, Narayanan A, Miller A, et al.Mixcoin:anonymity for bitcoin with accountable mixes[C]//International Conference on Financial Cryptography and Data Security.Berlin, Heidelberg:Springer, 2014:486-504.
[21] Valenta L, Rowan B.Blindcoin:blinded, accountable mixes for bitcoin[C]//International Conference on Financial Cryptography and Data Security.Berlin, Heidelberg:Springer, 2015:112-126.
[22] Ruffing T, Moreno-Sanchez P, Kate A.Coinshuffle:practical decentralized coin mixing for bitcoin[C]//European Symposium on Research in Computer Security.Cham:Springer, 2014:345-364.
[23] Ziegeldorf J H, Grossmann F, Henze M, et al.Coinparty:secure multi-party mixing of bitcoins[C]//Proceedings of the 5th ACM Conference on Data and Application Security and Privacy, 2015:75-86.
[24] Maxwell G.CoinSwap:transaction graph disjoint trustless trading.[EB/OL].(2013-08-22)[2021-11-16].https://bitcointalk.org/index.php.
[25] Sarada G, Abitha N, Manikandan G, et al.A few new approaches for data masking[C]//2015 International Conference on Circuits, Power and Computing Technologies, IEEE, 2015:1-4.
[26] Steichen M, Fiz B, Norvill R, et al.Blockchain-based, decentralized access control for IPFS[C]//2018 IEEE International Conference on Internet of Things and IEEE Green Computing and Communications and IEEE Cyber, Physical and Social Computing and IEEE Smart Data, 2018:1499-1506.DOI:10.1109/Cybermatics_2018.2018.00253.
[27] Chen Y, Li H, Li K, et al.An improved P2P file system scheme based on IPFS and blockchain[C]//2017 IEEE International Conference on Big Data, 2017:2652-2657.
[28] Zheng Q, Li Y, Chen P, et al.An innovative IPFS-based storage model for blockchain[C]//2018 IEEE/WIC/ACM International Conference on Web Intelligence, 2018:704-708.
[29] Androulaki E, Barger A, Bortnikov V, et al.Hyperledger Fabric:a distributed operating system for permissioned blockchains[C]//Proceedings of the Thirteenth EuroSys Conference, 2018:1-15.
[30] Gkountouna O, Terrovitis M.Anonymizing collections of tree-structured data[J].IEEE Transactions on Knowledge and Data Engineering, 2015, 27(8):2034-2048.
[31] Goldwasser S, Micali S, Rackoff C.The knowledge complexity of interactive proof systems[J].SIAM Journal on Computing, 1989, 18(1):186-208.
[32] Saberhagen N.Cryptonote V2.0[EB/OL].(2019-06-03)[2021-10-28].http://cryptonote.org/whitepaper.pdf.
[33] Rivest R L, Shamir A, Tauman Y.How to leak a secret[C]//International Conference on the Theory and Application of Cryptology and Information Security.Berlin, Heidelberg:Springer, 2001:552-565.
[34] Ruffing T, Moreno-Sanchez P, Kate A.Coinshuffle:practical decentralized coin mixing for bitcoin[C]//European Symposium on Research in Computer Security.Cham:Springer, 2014:345-364.
[35] Duffield E, Diaz D.Dash:a privacycentric cryptocurrency[EB/OL].2015[2021-10-28].https://docs.dash.org.
[36] Atzei N, Bartoletti M, Cimoli T.A survey of attacks on Ethereum smart contracts (Sok)[C]//International Conference on Principles of Security and Trust, 2017:164-186.
[37] Chang D Y.Applications of the extent analysis method on fuzzy AHP[J].European Journal of Operational Research, 1996, 95(3):649-655.
[38] Deng H P.Multicriteria analysis with fuzzy pairwise comparison[J].International Journal of Approximate Reasoning, 1999, 21(3):215-231.
[39] Mikhailov L.Deriving priorities from fuzzy pairwise comparison judgements[J].Fuzzy Sets and Systems, 2003, 134(3):365-385.
[40] Satty T.The analytic hierarchy process[M].New York:McGraw-Hill, 1980.
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