Computer Science ›› 2011, Vol. 38 ›› Issue (11): 87-91.
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LI Ken-li,KANG Qiang,TANG Zhuo,SHA Xing-mian,YANG Liu
Online:
Published:
Abstract: Access control is the main core policy of network security and protection, and its main task is to ensure that network resources arc not illegal use and access. Pulling the concept of the risk into access control, analysed delegate permissions based on risk and the basic nature of permissions of redistribution, and the calculation based on MUS collection, proposed a risk assessment based on neural network. Since the neural network is suited for the quantity data processing, and the risk factors arc of great uncertainty, the risk factors of information security were quantized by fuzzy evaluation method and the input of neural network was pretreatmented. The simulation results show that the trained neural network can estimate the degree of risk factor real time.
Key words: Access control, Risk assessment, Neural network, Fuzzy neural network
LI Ken-li,KANG Qiang,TANG Zhuo,SHA Xing-mian,YANG Liu. Access Control Policy Optimization Model Based on Neural Network[J].Computer Science, 2011, 38(11): 87-91.
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