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A security evaluation model for multi-source heterogeneous systems based on IOT and edge computing

Abstract

The deep integration and rapid development of new technologies such as edge computing and the Internet of Things (IoT) have brought new security challenges. Relying on mainstream security evaluation standards and security architecture, a security evaluation model for multi-source heterogeneous systems based on IoT and edge computing is proposed. An attribute-oriented security strategy decomposition system is established, and an indicator tree suitable for multi-source heterogeneous systems is constructed through mapping relationships. A comprehensive weighting method based on the optimal function theory is proposed. The weights are determined by the method based on indicator correlation and the method based on the amount of indicator information. According to the optimal function theory, the indicator weights obtained by the two methods are combined and optimized to obtain the optimal combination weight of the indicators. A comprehensive indicator measurement method based on the second-order grey cluster model is proposed, to deal with this situation of lack of persuasiveness in security ranking caused by the similar degree of membership in grey cluster evaluation. With this method, grey clustering of the initial score set can be used to obtain security evaluation results, and to rank the security evaluation results. According to the effectiveness evaluation indicator based on the discrimination coefficient and end-to-end consistency, the validity of the evaluation results is analyzed. Based on experiments, the model’s good performance in security evaluation and security ranking is verified.

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References

  1. 1.

    Liu, Y., Peng, M., Shou, G., Chen, Y., Chen, S.: Toward edge intelligence: multiaccess edge computing for 5g and internet of things. IEEE Internet Things J. 7(8), 6722–6747 (2020)

    Article  Google Scholar 

  2. 2.

    Liu, D., Yan, Z., Ding, W., Atiquzzaman, M.: A survey on secure data analytics in edge computing. IEEE Internet Things J. 6(3), 4946–4967 (2019)

    Article  Google Scholar 

  3. 3.

    Khurpade, J.M., Rao, D., Sanghavi, P.D.: A survey on iot and 5g network. In: 2018 International conference on smart city and emerging technology (ICSCET), pp. 1–3. IEEE (2018)

  4. 4.

    Hameed, A., Alomary, A.: Security issues in iot: A survey. In: 2019 International conference on innovation and intelligence for informatics, computing, and technologies (3ICT), pp. 1–5. IEEE (2019)

  5. 5.

    Gu, Z., Wang, Y., Shen, T., Lau, F.C.: On heterogeneous sensing capability for distributed rendezvous in cognitive radio networks. IEEE Trans. Mobile Comput. (2020). https://doi.org/10.1109/TMC.2020.2997077

    Article  Google Scholar 

  6. 6.

    Tian, Z., Shi, W., Wang, Y., Zhu, C., Du, X., Su, S., Sun, Y., Guizani, N.: Real-time lateral movement detection based on evidence reasoning network for edge computing environment. IEEE Trans. Ind. Inform. 15(7), 4285–4294 (2019)

    Article  Google Scholar 

  7. 7.

    Gu, Z., Su, Y., Liu, C., Lyu, Y., Jian, Y., Li, H., Cao, Z., Wang, L.: Adversarial attacks on license plate recognition systems. CMC-Comput. Mater. Continua 65(2), 1437–1452 (2020)

    Article  Google Scholar 

  8. 8.

    Hu, N., Tian, Z., Lu, H., Du, X., Guizani, M.: A multiple-kernel clustering based intrusion detection scheme for 5g and iot networks. Int. J. Mach. Learn. Cybern. 1–16 (2021)

  9. 9.

    Datta, P., Sharma, B.: A survey on iot architectures, protocols, security and smart city based applications. In: 2017 8th International conference on computing, communication and networking technologies (ICCCNT), pp. 1–5. IEEE (2017)

  10. 10.

    Xiao, Y., Jia, Y., Liu, C., Cheng, X., Yu, J., Lv, W.: Edge computing security: state of the art and challenges. Proc. IEEE 107(8), 1608–1631 (2019)

    Article  Google Scholar 

  11. 11.

    Wang, D., Bai, B., Lei, K., Zhao, W., Yang, Y., Han, Z.: Enhancing information security via physical layer approaches in heterogeneous iot with multiple access mobile edge computing in smart city. IEEE Access 7, 54508–54521 (2019)

    Article  Google Scholar 

  12. 12.

    Shirazi, S.N., Gouglidis, A., Farshad, A., Hutchison, D.: The extended cloud: review and analysis of mobile edge computing and fog from a security and resilience perspective. IEEE J. Sel. Areas Commun. 35(11), 2586–2595 (2017)

    Article  Google Scholar 

  13. 13.

    Qiu, J., Tian, Z., Du, C., Zuo, Q., Su, S., Fang, B.: A survey on access control in the age of internet of things. IEEE Internet Things J. 7(6), 4682–4696 (2020)

    Article  Google Scholar 

  14. 14.

    Ranaweera, P., Jurcut, A.D., Liyanage, M.: Survey on multi-access edge computing security and privacy. IEEE Commun. Surv. Tutor. 23(2), 1078–1124 (2021)

    Article  Google Scholar 

  15. 15.

    Ruan, Y., Durresi, A., Uslu, S.: Trust assessment for internet of things in multi-access edge computing. In: 2018 IEEE 32nd International conference on advanced information networking and applications (AINA), pp. 1155–1161. IEEE (2018)

  16. 16.

    Park, K.C., Shin, D.H.: Security assessment framework for iot service. Telecommun. Syst. 64(1), 193–209 (2017)

    Article  Google Scholar 

  17. 17.

    Lai, S., Zhao, R., Tang, S., Xia, J., Zhou, F., Fan, L.: Intelligent secure mobile edge computing for beyond 5g wireless networks. Phys. Commun. 45, 101283 (2021)

    Article  Google Scholar 

  18. 18.

    Peng, H., Kan, Z., Liu, C., Baker, T., Zhao, D.: Risk assessment of cps composed of edge consumer electronics under intentional attack. IEEE Consum. Electron. Mag. (2020). https://doi.org/10.1109/MCE.2020.3034066

    Article  Google Scholar 

  19. 19.

    Shrestha, M., Johansen, C., Noll, J.: Building confidence using beliefs and arguments in security class evaluations for iot. In: 2020 Fifth International conference on fog and mobile edge computing (FMEC), pp. 244–249. IEEE (2020)

  20. 20.

    Zhu, Z., Tian, Y., Li, F., Yang, H., Ma, Z., Rong, G.: Research on edge intelligence-based security analysis method for power operation system. In: 2020 7th IEEE international conference on cyber security and cloud computing (CSCloud)/2020 6th IEEE international conference on edge computing and scalable cloud (EdgeCom), pp. 258–263. IEEE (2020)

  21. 21.

    Huang, Y.L., Sun, W.L.: An ahp-based risk assessment for an industrial iot cloud. In: 2018 IEEE international conference on software quality, reliability and security companion (QRS-C), pp. 637–638. IEEE (2018)

  22. 22.

    Dorsemaine, B., Gaulier, J.P., Wary, J.P., Kheir, N., Urien, P.: A new threat assessment method for integrating an iot infrastructure in an information system. In: 2017 IEEE 37th international conference on distributed computing systems workshops (ICDCSW), pp. 105–112. IEEE (2017)

  23. 23.

    Part, C.: 2, common criteria for information technology security evaluation (version 3.1, revision 4) part 2: Part 2: security functional requirements (iso/iec 15408-2) (2012)

  24. 24.

    Hogan, M., Piccarreta, B., Group, I.I.C.S.W., et al.: Interagency report on status of international cybersecurity standardization for the internet of things (iot). Tech. rep., National Institute of Standards and Technology (2018)

  25. 25.

    Patel, M., Naughton, B., Chan, C., Sprecher, N., Abeta, S., Neal, A., et al.: Mobile-edge computing introductory technical white paper. White paper, mobile-edge computing (MEC) industry initiative 29, 854–864 (2014)

  26. 26.

    Sanming, P., Mingqiang, Y.: System and application of video surrveillance based on edge computing. Telecommun. Sci. 36(6), 64 (2020)

    Google Scholar 

  27. 27.

    Tseng, M., Canaran, T., Canaran, L.I.: Introduction to edge computing in iiot, pp. 1–19. Industrial Internet Consortium, Needham, MA (2018)

    Google Scholar 

  28. 28.

    Hassija, V., Chamola, V., Saxena, V., Jain, D., Goyal, P., Sikdar, B.: A survey on iot security: application areas, security threats, and solution architectures. IEEE Access 7, 82721–82743 (2019)

    Article  Google Scholar 

  29. 29.

    Langville, A.N., Meyer, C.D.: Google’s PageRank and Beyond: The Science of Search Engine Rankings. Princeton University Press, Princeton (2011)

    MATH  Google Scholar 

  30. 30.

    Zou, Z.H., Yi, Y., Sun, J.N.: Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. J. Environ. Sci. 18(5), 1020–1023 (2006)

    Article  Google Scholar 

  31. 31.

    Julong, D.: Introduction to grey system theory. J. Grey Syst. 1(1), 1–24 (1989)

    MathSciNet  MATH  Google Scholar 

  32. 32.

    Luo, H., Shen, Y., Zhang, G., Huang, L.: Information security risk assessment based on two stages decision model with grey synthetic measure. In: 2015 6th IEEE international conference on software engineering and service science (ICSESS), pp.795–798. IEEE (2015)

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Acknowledgements

This research is supported by the National Key R&D Program of China under Grant (No. 2019YFB2102400).

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Correspondence to Yueming Lu or Hui Lu.

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Guo, Z., Lu, Y., Tian, H. et al. A security evaluation model for multi-source heterogeneous systems based on IOT and edge computing. Cluster Comput (2021). https://doi.org/10.1007/s10586-021-03410-4

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Keywords

  • Multi-source heterogeneous systems
  • Security evaluation
  • IoT
  • Edge computing
  • Grey clustering model
  • Combination weighting method