The Dynamic Risk Assessment Of Power Information System Based On Data Fusion

The smart grid, which is the intelligent of the power grid, is one of the important means to promote the development of the renewable energy, to achieve energy-saving emission reduction and to realize sustainable development. Contrary to the traditional power grid, the structure of smart grid is more tremendous and its network environment is more complex. As a result, the smart grid will confront more network security threats. While traditional risk assessment on power information system has been difficult to deal with the massive amounts of network security threats that smart grid are faced with, so in the future, the research project on risk assessment will focus on the way to conduct a real-time, dynamic risk assessment on power information system.Based on the theories related to risk assessment of information security and the security features of power information system, in this paper, a dynamic risk assessment model has been established by introducing the improved genetic algorithm, the radial basis function neural network and theory of Hidden Markov. Using the analytic hierarchy process, the critical assets, vulnerabilities and threats of the evaluated system are identified and assigned by weight. Then collect network data and host information from servers and routers through distributed multi-node IDS agent. With dynamic update, the current level of threats and risk activities could be described in real-time, and the future risk trend could be forecasted.In order to carry out a dynamic risk assessment on power information system effectively, each attack is divided into three distinct phases in this paper. The difficulty of attack is assessed by percent of each attack time of distinct stages take up in the total attack time. Accordingly the state transition matrix of the assets is determined, and then the dynamic of risk assessment is realized. The real-time dynamic risk assessment methods based on Hidden Markov Model has strong adaptability and scalability, these methods can be applied to different levels of risk assessment effectively, such as internet, server, system, service and so on. By designing and realizing the dynamic risk assessment on power information system, the dynamic evaluation model is demonstrated. In addition, an analysis system on risk assessment is constructed, which has achieved the functions of analyzing and calculating the value of risk and has realized the function of risk management.