Abstract
At present, there are many threats to medical data security. Because of the different standards of data storage and system, it is very difficult to share medical data and protect data privacy. This paper proposes a data privacy protection method based on K-anonymity for medical alliance chain. The data privacy protection method of Medical Alliance chain in this paper consists of four steps: (1) constructing equivalent classes; (2) medical data slicing; (3) data iteration; (4) medical data reorganization. The scheme of data privacy protection in Medical Alliance chain proposed in this paper has high security, no trusted third party and low energy consumption. It is a privacy protection method suitable for application and medical alliance chain data.
Foundation Project: National Natural Science Foundation of China (61572036); Open Project of National Key Laboratory of Computer Architecture (CARCH201810).
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References
Sadeghi, A.R., Wachsmann, C., Waidner, M.: Security and privacy challenges in industrial internet of things. In: 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC), pp. 1–6. IEEE (2015)
Gan, G., Lu, Z., Jiang, J.: Internet of things security analysis. In: 2011 International Conference on Internet Technology and Applications, pp. 1–4. IEEE (2011)
Liu, Z., Chengli, Y.: Starting with Wannacry blackmail virus, this paper explores the security defense strategy of computer viruses in LAN. Secrecy Sci. Technol. 06, 19–22 (2017)
Chen, Q., Bridges, R.A.: Automated behavioral analysis of malware: a case study of wannacry ransomware. In: 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 454–460. IEEE (2017)
Wang, T., Liu, Y., Jinxin, et al.: Research on k-anonymity-based location and data privacy protection methods in group intelligence perception. J. Commun. 39(S1), 176–184 (2018)
Tian, Y., Li, X., Sangaiah, A.K., et al.: Privacy-preserving scheme in social participatory sensing based on secure multiparty cooperation. Comput. Commun. 119, 167–178 (2018)
Wang, C.J., Ku, W.S.: Anonymous sensory data collection approach for mobile participatory sensing. In: 2012 IEEE 28th International Conference on Data Engineering Workshops, pp. 220–227. IEEE (2012)
Xiao, Z., Yang, J.J., Huang, M., et al.: QLDS: a novel design scheme for trajectory privacy protection with utility guarantee in participatory sensing. IEEE Trans. Mob. Comput. 17(6), 1397–1410 (2017)
Acknowledgements
This research was supported by National Natural Science Foundation of China (No. 61572036) and National Key Laboratory of Computer Architecture (CARCH201810).
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Sun, H., Huang, C., Cheng, X., Chen, F. (2019). Data Privacy Protection in Medical Alliance Chain Based on K-Anonymity. In: Vaidya, J., Zhang, X., Li, J. (eds) Cyberspace Safety and Security. CSS 2019. Lecture Notes in Computer Science(), vol 11982. Springer, Cham. https://doi.org/10.1007/978-3-030-37337-5_20
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DOI: https://doi.org/10.1007/978-3-030-37337-5_20
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