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ACMDS: An Anonymous Collaborative Medical Data Sharing Scheme Based on Blockchain

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Web and Big Data (APWeb-WAIM 2024)

Abstract

Electronic Health Records (EHRs) play a crucial role in improving healthcare efficiency and quality through data sharing between healthcare institutions and patients. The sharing of EHRs necessitates collaboration, especially in emergency cases where patients require treatment across different institutions. Given that EHRs typically contain sensitive personal information, they require a delicate balance between data collaborative accessibility and privacy protection. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) that supports collaborative decryption facilitates secure, fine-grained, and collaborative access, while maintaining data confidentiality. However, challenges persist in collaborative scenarios, such as identity inference attacks and the hesitancy of healthcare institutions to share EHRs. In this paper, we propose an anonymous collaborative medical data sharing scheme based on blockchain (ACMDS), and introduce an enhanced attribute-based, anonymous collaborative access control approach. Our scheme secures the identity privacy of collaborators by employing the ring signature, and effectively prevents node deception through the mapping established by the smart contract. Security analysis confirms ACMDS’s robustness in preserving data privacy, fostering collaboration, safeguarding identity anonymity, and enabling auditability. Performance evaluations demonstrate ACMDS’s practicality and efficacy in a healthcare context.

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References

  1. Liu, Y., Ma, Z., Liu, X., et al.: Privacy-preserving object detection for medical images with faster R-CNN. IEEE Trans. Inf. Forensics Secur. 17, 69–84 (2019). https://doi.org/10.1109/TIFS.2019.2946476

    Article  Google Scholar 

  2. Narayan, S., Gagné, M., Safavi-Naini, R.: Proceedings of the. ACM Workshop on Cloud Computing Security Workshop, vol. 2010, pp. 47–52 (2010). https://doi.org/10.1145/1866835.1866845

  3. Bethencourt, J., Sahai, A., Waters, B.: Ciphertext-policy attribute-based encryption. In: 2007 IEEE Symposium on Security and Privacy (SP 2007), pp. 321-334. IEEE (2007). https://doi.org/10.1109/SP.2007.11

  4. Xue, Y., Xue, K., Gai, N., et al.: An attribute-based controlled collaborative access control scheme for public cloud storage. IEEE Trans. Inf. Forensics Secur. 14(11), 2927–2942 (2019). https://doi.org/10.1109/TIFS.2019.2911166

    Article  Google Scholar 

  5. Li, M., Huang, X., Liu, J.K., Xu, L.: GO-ABE: group-oriented attribute-based encryption. In: Au, M.H., Carminati, B., Kuo, C.-C.J. (eds.) NSS 2014. LNCS, vol. 8792, pp. 260–270. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11698-3_20

    Chapter  Google Scholar 

  6. Bobba, R., Khurana, H., Prabhakaran, M.: Attribute-sets: a practically motivated enhancement to attribute-based encryption. In: Backes, M., Ning, P. (eds.) ESORICS 2009. LNCS, vol. 5789, pp. 587–604. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04444-1_36

    Chapter  Google Scholar 

  7. Shen, J., Zhou, J., Xie, Y., Yu, S., Xuan, Q.: Identity inference on blockchain using graph neural network. In: Dai, H.-N., Liu, X., Luo, D.X., Xiao, J., Chen, X. (eds.) BlockSys 2021. CCIS, vol. 1490, pp. 3–17. Springer, Singapore (2021). https://doi.org/10.1007/978-981-16-7993-3_1

    Chapter  Google Scholar 

  8. Noether, S., Mackenzie, A.: Ring confidential transactions. Ledger 1, 1–18 (2016). https://doi.org/10.5195/ledger.2016.34

    Article  Google Scholar 

  9. Green, M., Hohenberger, S., Waters, B.: Outsourcing the decryption of ABE ciphertexts. In: 20th USENIX Security Symposium (USENIX Security 2011), pp. 1-16 (2011)

    Google Scholar 

  10. Waters, B.: Ciphertext-Policy attribute-based encryption: an expressive, efficient, and provably secure realization. In: Catalano, D., Fazio, N., Gennaro, R., Nicolosi, A. (eds.) PKC 2011. LNCS, vol. 6571, pp. 53–70. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19379-8_4

    Chapter  Google Scholar 

  11. Jin, Y., Tian, C., He, H., et al.: A secure and lightweight data access control scheme for mobile cloud computing. In: 2015 IEEE Fifth International Conference on Big Data and Cloud Computing, pp. 172-179. IEEE, (2015). https://doi.org/10.1109/BDCloud.2015.57

  12. Li, J., Huang, Q., Chen, X., et al.: Multi-authority ciphertext-policy attribute-based encryption with accountability. In: Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security. pp. 386-390 (2011). https://doi.org/10.1145/1966913.1966964

  13. Xhafa, F., Feng, J., Zhang, Y., et al.: Privacy-aware attribute-based PHR sharing with user accountability in cloud computing. J. Supercomput. 71, 1607–1619 (2015). https://doi.org/10.1007/s11227-014-1253-3

    Article  Google Scholar 

  14. Li, M., Yu, S., Zheng, Y., et al.: Scalable and secure sharing of personal health records in cloud computing using attribute-based encryption. IEEE Trans. Parallel Distrib. Syst. 24(1), 131–143 (2012). https://doi.org/10.1109/TPDS.2012.97

    Article  Google Scholar 

  15. Li, F., Liu, K., Zhang, L., et al.: Ehrchain: a blockchain-based ehr system using attribute-based and homomorphic cryptosystem. IEEE Trans. Serv. Comput. 15(5), 2755–2765 (2021). https://doi.org/10.1109/TSC.2021.3078119

    Article  Google Scholar 

  16. Wang, M., Guo, Y., Zhang, C., et al.: MedShare: a privacy-preserving medical data sharing system by using blockchain. IEEE Trans. Serv. Comput., 438–451 (2021). https://doi.org/10.1109/TSC.2021.3114719

  17. Li, P., Zhou, D., Ma, H., et al.: Flexible and secure access control for EHR sharing based on blockchain. J. Syst. Architect. 146, 103033 (2024). https://doi.org/10.1016/j.sysarc.2023.103033

    Article  Google Scholar 

  18. Yin, H., Zhao, Y., Zhang, L., et al.: Attribute-based searchable encryption with decentralized key management for healthcare data sharing. J. Syst. Architect. 148, 103081 (2024). https://doi.org/10.1016/j.sysarc.2024.103081

    Article  Google Scholar 

  19. Nakamoto, S.: Bitcoin: A peer-to-peer electronic cash system. Decentralized Bus. Rev. (2008). https://doi.org/10.2139/ssrn.3440802

    Article  Google Scholar 

  20. Wang, H., Ge, C., Zhou, L., et al.: A publicly verifiable outsourcing matrix computation scheme based on smart contracts. IEEE Trans. Cloud Comput. (2023). https://doi.org/10.1109/tcc.2023.3337848

    Article  Google Scholar 

  21. Xu, G., Qi, C., Dong, W., et al.: A privacy-preserving medical data sharing scheme based on blockchain. IEEE J. Biomed. Health Inform. 27(2), 698–709 (2022). https://doi.org/10.1109/JBHI.2022.3203577

    Article  Google Scholar 

  22. Dai, W., Tuo, S., Yu, L., et al.: HAPPS: a hidden attribute and privilege-protection data-sharing scheme with verifiability. IEEE Internet Things J. 9(24), 25538–25550 (2022). https://doi.org/10.1109/JIOT.2022.3197708

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Key R&D Program of China (2021YFB2700503), the National Natural Science Foundation of China (62071222, 62076125 , 62032025, U21A20467, U20A20176, U22B2030 ), the Shenzhen Science and Technology Program (JCYJ20210324134810028, JCYJ20210324134408023), and the Natural Science Foundation of Jiangsu Province BK20220075.

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Correspondence to Lu Zhou .

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Wang, Y., Tao, Y., Wang, H., Ge, C., Zhou, L. (2024). ACMDS: An Anonymous Collaborative Medical Data Sharing Scheme Based on Blockchain. In: Zhang, W., Tung, A., Zheng, Z., Yang, Z., Wang, X., Guo, H. (eds) Web and Big Data. APWeb-WAIM 2024. Lecture Notes in Computer Science, vol 14964. Springer, Singapore. https://doi.org/10.1007/978-981-97-7241-4_17

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  • DOI: https://doi.org/10.1007/978-981-97-7241-4_17

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