Design of Industrial Network Security Situation Awareness Method Based on Deep Neural Network
Industrial networks are constantly facing various attack and intrusion risks from the network.To protect the security of industrial networks,a deep neural network-based industrial network security situational awareness method is designed.In this de-sign,data warehousing integration technology is used to integrate the situation information required for deep neural network input and implement processing.The Analytic Hierarchy Process is used to extract key situation elements from the basic information,and the key situation elements are used as inputs.The deep neural network is used to calculate the industrial network security situation value and classify the security situation level.The results show that as the attack progresses,the security situation value of industrial net-works shows an upward trend,with the situation value under U2R attack increasing from 0.32 to 0.86,and the situation level develo-ping from secure to high-risk;Under DDos attacks,the situational value has increased from 0.47 to 0.55,and the situational level has evolved from safe to medium risk;The situation value does not change significantly under the Porbe attack,and the situation level has always been at the security level,indicating that the industrial network has the strongest protection ability against Porbe attacks and the weakest protection ability against U2R attacks.
deep neural networkindustrial networksecurity situationperception methods
万方数据
维普
