Research On Neuron Model Of Analytical Factors For Safety And Defense Of SCADA In Oil And Gas Gathering And Transportation

SCADA (Supervisory Control and Data Acquisition) system has been widely used in oil&gas gathering and transportation field, especially in large scale oil&gas gathering and transferring pipeline network. In the past, the SCADA system has been in a closed environment, the security risk of which is relatively low. In recent years, for economic, political and military reasons, SCADA in energy field get frequent attacks from hostile countries and groups. SCADA of oil and gas gathering and transportation, as an important part of the national crucial infrastructures and energy development strategy, faces serious security challenges.The research of this Paper is sub-project of the National Natural Science Foundation Project, Modeling Theory and Simulation Research of Large-scale Oil and Gas Gathering and Transferring Pipeline SCADA Security Defense System Based on Factor Neural Network (FNN). Focusing on implementation of oil and gas gathering and transferring SCADA security defense method based on FNN, this paper analyzes the differences between the SCADA and the traditional information system and pointcut for security defense of SCADA system. Using the analytical factor neuron as the basic unit in the implementation of security defense, this paper focus on the research of the model and implementation of prototype.Compared with the traditional IT system, oil and gas gathering and transferring SCADA system has a wide geographical distribution, the edge part of which are sensors or control devices with a low degree of intelligence, rather than the general computer in the conventional sense. In addition, with distributed characteristics, the structure of SCADA system has a high vertical integration and the master node and terminal node is Hypotactic, instead of flat and equivalent in IT system. Besides, for those organized and specific unknown attacks from outside, the products with conventional passive defense don’t work. Because of the High requirements about The real-time and stability of SCADA system on the production and control, conventional security products are not allowed, which is also different from the traditional IT system. Therefore, the traditional means for IT system’s security is not completely suitable for SCADA system.According to the characteristics of oil and gas gathering and transferring SCADA and combined with the factor neural network theory, this paper takes security defense of the host in SCADA as a pointcut and explores and constructs the general the analytical factor neuron model to achieve the security defense of SCADA. Factor neuron model implemented by using the intelligent agent technology have cross platform and distributed characteristics, and have strong mobility and scalability to meet the needs of security defense of SCADA, which is helpful to the intelligentized deployment in the large scale oil and gas gathering and transferring SCADA security defense system. In addition, compared with the traditional passive defense method of character code matching, this model is based on proactive defense technology by capturing the programs’behaviors, has the ability to resist the unknown attacks and some specific attacks. Finally, according to the constructed general model, this paper implements the Identify Neuron which do the main defense tasks and the confirmatory tests are done, which verifies the feasibility of the model. The work done in this paper is original and the establishment of the prototype system has a certain practical value for research and exploration about security defense of oil and gas gathering and transferring SCADA. It also opens up a new way for further research about establishing a security defense system for SCADA.