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Research on key technologies of data security and privacy protection in Internet of Things group intelligence

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Abstract

With the increasing scale and complexity of IoT swarm intelligence applications, data security and privacy protection have become important factors restricting the development of IoT swarm intelligence. This paper explores the key technologies of data security and privacy protection in IoT swarm intelligence to improve the security and trustworthiness of IoT swarm intelligence applications. Using the method of literature research and empirical analysis, the data security and privacy protection in the swarm intelligence of the Internet of Things are deeply analyzed and studied. The data security risks in the Internet of Things are identified and classified, and the corresponding security requirements are proposed. According to different security requirements, a series of data security and privacy protection technologies are proposed. Finally, through empirical research, the effectiveness and feasibility of the proposed key technologies are verified. The research results show that these technologies and methods can provide guarantees for the security and trustworthiness of IoT swarm intelligence applications, contributing to the healthy development of the IoT industry. However, further research and improvements are still needed to address new security and privacy challenges that continue to emerge.

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References

  • Abowd, J.M., Schmutte, I.M.: An economic analysis of privacy protection and statistical accuracy as social choices. Am. Econ. Rev. 109(1), 171–202 (2019)

    Article  Google Scholar 

  • Choi, J., Sung, W., Choi, C., Kim, P.: Personal information leakage detection method using the inference-based access control model on the android platform. Pervasive Mob. Comput. 24, 138–149 (2015)

    Article  Google Scholar 

  • Dong, J., Roth, A., Su, W.J.: Gaussian differential privacy. J. R. Stat. Soc. Ser. B Stat Methodol. 84(1), 3–37 (2022)

    Article  MathSciNet  Google Scholar 

  • Elkoumy, G., Fahrenkrog-Petersen, S.A., Sani, M.F., et al.: Privacy and confidentiality in process mining: threats and research challenges. ACM Trans. Manag. Inf. Syst. (TMIS) 13(1), 1–17 (2021)

    Google Scholar 

  • Feng, X., Yan, F., Liu, X.: Study of wireless communication technologies on internet of things for precision agriculture. Wireless Pers. Commun. 108(3), 1785–1802 (2019a)

    Article  Google Scholar 

  • Feng, Q., He, D., Zeadally, S., et al.: A survey on privacy protection in blockchain system. J. Netw. Comput. Appl. 126, 45–58 (2019b)

    Article  Google Scholar 

  • Ju, C., Gu, Q., Wu, G., Zhang, S.: Local differential privacy protection of high-dimensional perceptual data by the refined Bayes network. Sensors 20(9), 208–216 (2020)

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  • Paul, A., Jeyaraj, R.: Internet of Things: a primer. Human Behav. Emerg. Technol. 1(1), 37–47 (2019)

    Article  Google Scholar 

  • Ray, P.P.: A survey on internet of things architectures. J. King Saud Univ. Comput. Inf. Sci. 30(3), 291–319 (2018)

    Google Scholar 

  • Shuman, E., Saguy, T., van Zomeren, M., Halperin, E.: Disrupting the system constructively: testing the effectiveness of nonnormative nonviolent collective action. J. Pers. Soc. Psychol. 121(4), 785–796 (2021)

    Article  PubMed  Google Scholar 

  • Sugiura, G., Ito, K., Kashima, K.: Bayesian differential privacy for linear dynamical systems. IEEE Control Syst Lett 6, 896–901 (2021)

    Article  MathSciNet  Google Scholar 

  • Sun, P.: Security and privacy protection in cloud computing: discussions and challenges. J. Netw. Comput. Appl. 160, 5434–5439 (2020)

    Article  Google Scholar 

  • Yang, P., Xiong, N., Ren, J.: Data security and privacy protection for cloud storage: a survey. IEEE Access 8, 131723–131740 (2020)

    Article  Google Scholar 

  • Yu, K., Guo, Z., Shen, Y., et al.: Secure artificial intelligence of things for implicit group recommendations. IEEE Internet Things J. 9(4), 2698–2707 (2021)

    Article  Google Scholar 

  • Zhao, Y., Chen, J.: A survey on differential privacy for unstructured data content. ACM Comput. Surv. (CSUR) 54(10s), 1–28 (2022)

    Article  Google Scholar 

Download references

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The first version was written by YL, YH and QC has done the simulations. All authors have contributed to the paper’s analysis, discussion, writing, and revision.

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Correspondence to Yadong Liu.

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Liu, Y., Hua, Y. & Chen, Q. Research on key technologies of data security and privacy protection in Internet of Things group intelligence. Opt Quant Electron 56, 114 (2024). https://doi.org/10.1007/s11082-023-05691-y

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