Research On Key Technologies Of Cloud Platform Security Situation Assessment

With the development of cloud computing technology,the attacks and sabotage behaviors that cloud platforms suffer in their daily operations have gradually increased,and cloud computing security has received more and more attention.In recent years,the security incidents of cloud computing service platforms have never stopped.Malicious attacks,server interruptions,and data loss are all very troublesome security issues for cloud platforms.The structure of the cloud platform is relatively special and complex.The application of network security situation assessment technology to the cloud platform can accurately assess the security status of the cloud platform network operation,and the final result can enable the cloud platform administrator to manage There is an intuitive and accurate data reference for cloud platform security,which can predict and respond in advance before security problems occur on the cloud platform to minimize losses.Therefore,studying the application of network security situation assessment technology in cloud platform security protection has important practical significance and economic value.The research content mainly includes the following three aspects:(1)First,it studies and analyzes the traditional situation assessment models and methods,the development status and existing problems of the key technologies of cloud platform network security situation assessment.On this basis,a hierarchical cloud platform comprehensive situation assessment model is proposed.This model not only considers the situation assessment of cloud platform network traffic and attack behavior,but also integrates the virtual layer and host layer that are relatively ignored in the existing situation assessment model.(2)An improved adaptive genetic simulated annealing algorithm(OAGSAA)is proposed for the situation assessment of the non-host layer.The algorithm optimizes the selection,crossover,mutation probability determination and Metropolis criterion,which can quickly solve the optimal individual and avoid premature maturity.phenomenon.On this basis,the OAGSAA-BP algorithm that optimizes the BP neural network is proposed,which can determine the optimal initial weight threshold of the BP neural network,and realize the effective evaluation of the security status of the cloud platform's non-host layer.At the same time,a host-level situation assessment algorithm based on uncertainty reasoning is designed and implemented.(3)The overall situation fusion method of the cloud platform based on the gray correlation theory is proposed,and the calculation method of the difference matrix is optimized.The situation value of the overall cloud platform is obtained by calculating the gray correlation degree between the various layers of the situation and performing a weighted sum.Conduct a comprehensive situation assessment of the cloud platform.Finally,simulation experiments are used to verify the effectiveness of the non-host layer and host layer situation assessment methods of the cloud platform and the effectiveness of the cloud platform situation fusion method.The experimental results show that the proposed cloud platform situation assessment method has higher accuracy and faster evaluation speed for cloud platform situation assessment,and overcomes the limitations of some traditional algorithms.The cloud platform situation fusion algorithm can realize a comprehensive assessment of the overall situation of the cloud platform.