A verifiable EVM-based cross-language smart contract implementation scheme for matrix calculation

Abstract

The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses, which involve the calculation of complex functions, such as matrix operations. However, complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine (EVM)-based smart contract platforms due to their distributed security environment limitations. Existing off-chain methods often result in a significant reduction in contract execution efficiency, thus a platform software development kit interface implementation method has become a feasible way to reduce overheads, but this method cannot verify operation correctness and may leak sensitive user data. To solve the above problems, we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations, especially matrix operations, which can guarantee operation correctness and user privacy while ensuring computational efficiency. In this scheme, a verifiable interaction process is designed to verify the computation process and results, and a matrix blinding technology is introduced to protect sensitive user data in the calculation process. The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.

Keywords

Smart contract / Blockchain / Cross-language programming / Bilinear pairing / Publicly verifiable computation

CRediT authorship contribution statement

Yunhua He: Methodology, Writing - original draft, Writing - review & editing. Yigang Yang: Data curation, Methodology. Chao Wang: Validation, Writing - review & editing. Anke Xie: Funding acquisition, Writing - review & editing. Li Ma: Conceptualization, Writing - review & editing. Bin Wu: Methodology, Writing - review & editing. Yongdong Wu: Project administration, Writing - review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 62272007, U23B2002, in part by the Excellent Young Talents Project of the Beijing Municipal University Teacher Team Construction Support Plan under Grant BPHR202203031, in part by the Yunnan Key Laboratory of Blockchain Application Technology under Grant 2021105AG070005(YNB202102), and in part by the Open Topics of Key Laboratory of Blockchain Technology and Data Security, The Ministry of Industry and Information Technology of the People's Republic of China under Grant 20243222.

References

[1] W. Zou, D. Lo, P.S. Kochhar, X.-B.D. Le, X. Xia, Y. Feng, Z. Chen, B. Xu, Smart contract development: challenges and opportunities, IEEE Trans. Softw. Eng. 47 (10) (2021) 2084-2106.

[2] C. Qiu, H. Yao, C. Jiang, S. Guo, F. Xu, Cloud computing assisted blockchain-enabled Internet of things, IEEE Trans. Cloud Comput. 10 (1) (2022) 247-257.

[3] J. Lindsay, Smart contracts for incentivizing sensor based mobile smart city applica-tions, in: 2018 IEEE International Smart Cities Conference (ISC2), 2018, pp. 1-4.

[4] J. Wu, S. Guo, H. Huang, W. Liu, Y. Xiang, Information and communications tech-nologies for sustainable development goals: state-of-the-art, needs and perspectives, 20 (3) (2018) 2389-2406.

[5] G. Liu, J. Wu, T. Wang, Blockchain-enabled fog resource access and granting, Intell. Converg. Netw. 2 (2) (2021) 108-114.

[6] J. Chen, X. Xia, D. Lo, J. Grundy, X. Luo, T. Chen, Defining smart contract defects on Ethereum, IEEE Trans. Softw. Eng. 48 (1) (2022) 327-345.

[7] D. Lin, J. Wu, Q. Yuan, Z. Zheng, Modeling and understanding Ethereum transaction records via a complex network approach, IEEE Trans. Circuits Syst. II, Express Briefs 67 (11) (2020) 2737-2741.

[8] E. Ben Sasson, A. Chiesa, C. Garman, M. Green, I. Miers, E. Tromer, M. Virza, Ze-rocash: decentralized anonymous payments from bitcoin, in: 2014 IEEE Symposium on Security and Privacy, IEEE, 2014, pp. 459-474.

[9] S. Albawi, T.A. Mohammed, S. Al-Zawi,Understanding of a convolutional neural network, in:2017 International Conference on Engineering and Technology (ICET), 2017, pp. 1-6.

[10] Y. Yan, T. Hayakawa,Bifurcation analysis and tax/subsidy approach in noncoop-erative dynamical systems, in:2019 American Control Conference (ACC), 2019, pp. 2303-2308.

[11] S. Han, X. Liu, H. Mao, J. Pu, A. Pedram, M.A. Horowitz, W.J. Dally, Eie: effi-cient inference engine on compressed deep neural network,in: 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA), 2016, pp. 243-254.

[12] V. Badrinarayanan, A. Kendall, R. Cipolla, Segnet: a deep convolutional encoder-decoder architecture for image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. 39 (12) (2017) 2481-2495.

[13] S. Sridhar, S. Sanagavarapu, Analysis of smart contract abstraction in decentralized blockchain based stock exchange, in: 2021 IEEE World AI IoT Congress (AIIoT), 2021, pp. 0397-0406.

[14] C. Dong, C.C. Loy, K. He, X. Tang, Image super-resolution using deep convolutional networks, IEEE Trans. Pattern Anal. Mach. Intell. 38 (2) (2016) 295-307.

[15] A. Juels, C. Tech, N. York, The ring of gyges: using smart contracts for crime, General Information (2015) 1-32.

[16] J. Chen, X. Xia, D. Lo, J. Grundy, X. Yang, Maintenance-related concerns for post-deployed Ethereum smart contract development: issues, techniques, and future chal-lenges, 26 (117) (2021), https://doi.org/10.1007/s10664-021-10018-0.

[17] M. Li, J. Weng, A. Yang, W. Lu, Y. Zhang, L. Hou, J.-N. Liu, Y. Xiang, R.H. Deng, Crowdbc: a blockchain-based decentralized framework for crowdsourcing, IEEE Trans. Parallel Distrib. Syst. 30 (6) (2019) 1251-1266.

[18] G. Zyskind, O. Nathan, A.S. Pentland,Decentralizing privacy: using blockchain to protect personal data, in: 2015 IEEE Security and Privacy Workshops, 2015, pp. 180-184.

[19] J. Huang, L. Kong, G. Chen, M.-Y. Wu, X. Liu, P. Zeng, Towards secure industrial iot: blockchain system with credit-based consensus mechanism, IEEE Trans. Ind. Inform. 15 (6) (2019) 3680-3689.

[20] J.C. López-Pimentel, O. Rojas, R. Monroy,Blockchain and off-chain: a solution for audit issues in supply chain systems, in: 2020 IEEE International Conference on Blockchain (Blockchain), 2020, pp. 126-133.

[21] E. Leka, B. Selimi, L. Lamani, Systematic literature review of blockchain applica-tions: smart contracts,in: 2019 International Conference on Information Technolo-gies (InfoTech), 2019, pp. 1-3.

[22] S. Wang, L. Ouyang, Y. Yuan, X. Ni, X. Han, Blockchain-enabled smart contracts: architecture, applications, and future trends, IEEE Trans. Syst. Man Cybern. Syst. 49 (2019) 2266-2277.

[23] K. Christidis, M. Devetsikiotis, Blockchains and smart contracts for the Internet of things, IEEE Access 4 (2016) 2292-2303.

[24] X. Liu, R. Chen, Y.-W. Chen, S.-M. Yuan, Off-chain data fetching architecture for Ethereum smart contract, in: 2018 International Conference on Cloud Computing, Big Data and Blockchain (ICCBB), 2018, pp. 1-4.

[25] B. Ampel, M. Patton, H. Chen, Performance modeling of hyperledger sawtooth blockchain, in: 2019 IEEE International Conference on Intelligence and Security Informatics (ISI), 2019, pp. 59-61.

[26] H. Li, C. Li, H. Li, X. Bai, X. Shi, Fisco bcos technology application practice (in Chi-nese), Inf. Commun. Technol. Policy 46 (1) (2020) 52-60.

[27] J. Zhang, J. Cui, H. Zhong, Z. Chen, L. Liu, Pa-crt: Chinese remainder theorem based conditional privacy-preserving authentication scheme in vehicular ad-hoc networks, IEEE Trans. Dependable Secure Comput. 18 (2) (2021) 722-735.

[28] X. Chen, X. Huang, J. Li, J. Ma, W. Lou, D.S. Wong, New algorithms for secure outsourcing of large-scale systems of linear equations, IEEE Trans. Inf. Forensics Secur. 10 (1) (2015) 69-78.

[29] X. Zhang, T. Jiang, K.-C. Li, A. Castiglione, X. Chen, New publicly verifiable compu-tation for batch matrix multiplication, Inf. Sci. 479 (2019) 664-678.

[30] S. Salinas, C. Luo, X. Chen, P. Li, Efficient secure outsourcing of large-scale linear systems of equations, in: 2015 IEEE Conference on Computer Communications (IN-FOCOM), 2015, pp. 1035-1043.

[31] J. Duan, J. Zhou, Y. Li, Secure and verifiable outsourcing of large-scale nonnegative matrix factorization (nmf), IEEE Trans. Serv. Comput. 14 (6) (2021) 1940-1953.

[32] Q. Liu, Y. Tian, J. Wu, T. Peng, G. Wang, Enabling verifiable and dynamic ranked search over outsourced data, IEEE Trans. Serv. Comput. 15 (1) (2022) 69-82.

[33] M. Wohrer, U. Zdun, Smart contracts: security patterns in the Ethereum ecosystem and solidity,in: 2018 International Workshop on Blockchain Oriented Software En-gineering (IWBOSE), 2018, pp. 2-8.

[34] J. Katz, Y. Lindell, Introduction to Modern Cryptography, Chapman and Hall/CRC, 2007.