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Most cybersecurity frameworks are based on three major components such as confidentiality, integrity, and availability. All these components have their parameters that are used to secure network nodes. But finding the most cyber secure node in a network needs a measurement method. The aim of the paper is to offer a model that can be used to find the most secure network nodes considering these cybersecurity components and their parameters. This is achieved by modelling numeric values of respective weights for parameters of confidentiality, integrity, and availability. The model is applied to a simulated environment where random values standing for cybersecurity parameters are given to 30 wireless network nodes that are used as an example. Then the weighted values are processed with Python programming language by giving the most secure nodes according to needed cybersecurity components. This model can be used to recommend the right network node that can be used to deploy services securely while avoiding potential vulnerabilities and cyber-attacks.

Edge or fog computing are being used to reduce latency between end devices and traditional cloud computing. The latest developments that have improved the hardware aspects of wireless sensors and mobile networks, gave the opportunity for other enhancements if such technologies are integrated between them. Regarding this enhanced heterogeneous environment, the approach of placing services needs to reconsider the security aspects. We have developed a baseline method of a solution which fulfills the cybersecurity requirements converging with the proposed multi-tier integrated model, that enhances the K-means algorithm with added processing steps supplying the criteria of the CIA triad.