Biblio

The advent of Internet and recent technological developments have paved the way for IoT devices in different sectors. The demand for real-time response led to the development of fog computing which is now a popular computing technique. It provides processing, computing and storage at the network edge for latency-sensitive applications such as banking transactions, healthcare etc. This has further led to the pool of user's sensitive data across the web that needs to be secured. In order to find an efficient security solution, it is mandatory to prioritize amongst different fog-level security factors. The authors have therefore, adopted a fuzzy-based Analytical Hierarchy Approach (AHP) for ranking the security attributes in fog-driven IoT environment. The results have also been compared to the ones obtained from classical-AHP and are found to be correlated.

With the increasing security threats to the information of Industrial Cyber-physical Control Systems, the quantitative assessment of security risk becomes an important basis of information security research. Based on fuzzy hierarchy analysis, this paper constructs the hierarchical model of industrial control system safety risk evaluation, and obtains the exact value of risk. Experimental results show that the proposed method can effectively quantify the control system risk, which provides a basis for industrial control system risk management decision.