Simulation of Attack Signal Path Identification in Radio Network Information

Abstract

It is possible to improve the safety performance of the radio network by accurately identifying the attack signal path in the radio network information. When the attack signal path identification is carried out, it is necessary to calculate the vulnerability of the attack signal path, obtain the time series sample set of the net-work attack path, train the sample set for different vulnerabilities, and complete the path recognition.The traditional method is to establish the attack graph model. It cannot calculate the vulnerability of the attack signal path and cannot carry out the training, which leads to the limitation of the path recognition and the low efficiency. An improved identification method of attack signal path in radio network information with improved attack graph is proposed. Firstly, the attack map of the traditional method is transformed according to the theory of graph theory, and the concept of vulnerability factor is introduced into the improved attack graph. The vulnerability of the attack route is improved, and then the sliding time window is used to construct the network attack path recognition Time series sample set, Ada-Boosting method is used to train the sample sets with different vulnerabilities,and the regression matrix is obtained by using the training results. Finally, the attack signal path identification in the radio network information is completed.The simulation results show that the improved method has high accuracy and can guarantee the smooth operation ofthe radio network.