Model of risk assessment of information security based on fuzzy neural network
Junpeng Zhang · Computer Engineering and Applications Journal · 2009
Evaluating risk effectively,selecting effective defence measures and defending information threats actively are the key points of resolving security problems of information system.Based on the actual requirements and status of risk assessment of information security,we integrate the neural network and fuzzy logic to apply them in studying risk assessment of information security.Firstly,focused on the uncertainty and complexity of risk assessment of information security,we integrate the neural network to apply them in studying risk assessment.On the other hand,since the neural network is suited for the quantity data processing,and poor to the qualitative analyze,and risk is uncertain,the risk factors are quantized by fuzzy evaluation method proposed in this dissertation so that the input of neural network are pre-treated,a risk assessment method based on fuzzy neural network is proposed.The simulation results show that the trained neural network can estimate the degree of risk factor real time.