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


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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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).

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