Research On FNN Model Factor Neurons In SCADA System Security Defense

This study is a subproject of the national natural science fund project that named research of the modeling theory and simulation method of the massive pipeline network SCADA (Supervisory Control And Data Acquisition) security defense system based on FNN (factor neural network). In this subject, the factor neural network is used to solve the problem of SCADA system information security. In this paper, analytic factor neuron is studied. Analytic factor neuron is a component of the factor neural network which is one of the many factor neurons.SCADA system is a computer-based process control and dispatching automation system. SCADA system has a wide application in data acquisition and supervisory control in many fields such as metallurgy, oil chemical, electric power, railway, aviation and food processing industry etc. SCADA system is the nerve center of industrial control system. Since the "Stuxnet" virus incident of 2010, SCADA system of information security issues are paid close attention to all countries.Compared with the traditional information system, SCADA system with dedicated hardware, software and communication protocol, is isolation with the outside network world in physics. SCADA system has the characteristics of dispersed control and Centralized management. Compared with the traditional information system security defense, SCADA system security defense is more complicated. The traditional information system security means is difficult to completely solving the problem of the safety of the SCADA system. The Factors Neural Network theory is proposed, which in order to provide a new means and methods that solve this kind of complex system security defense.In view of the current SCADA system, the SCADA system and SCADA system network structure are introduced. A potential safety hazard of the SCADA system is analyzed and the reasoning mechanism of the SCADA system security defense is researched. Combined with Factor Neural Network theory, the knowledge base of the SCADA system security defense is constructed and a kind of hierarchical structure of factors neurons defense model is proposed. The specific safety protection measures are performed in the areas, such as the SCADA network communication field, SCADA software etc.Factor neuron defense model is realized based on mobile intelligent agent technology. Therefore, it, compared with the traditional security defense technology, has strong flexibility, mobility, scalability and other features. At the same time, the model has a cross-platform characteristics and distributed characteristics, which is very suitable for the demand of the SCADA system security defense. The factor neurons in each layer of the model are configured, reasonably, which can effectively ensure the security of SCADA system.