A Dynamic Monitoring Method of Social Network Worm Attack Based on Improved Decision Tree

Abstract

In the network security, worms are a kind of more aggressive virus, it is necessary to carry out a detailed discussion of worm attacks. There is a problem that the number of immune nodes is small in the application of worm attack dynamic monitoring method of social network, so a new method based on improved decision tree is designed. According to the attack infiltration theory and propagation mechanism, the worm type is identified, the worm propagation path is extracted, the copy of the worm program is transmitted to the adjacent nodes, and the heterogeneous model of topology structure is constructed by using the improved decision tree. Then the control is transferred to the function called to execute, and the dynamic monitoring mode of the worm attack is optimized. Experimental results show that the average immune nodes of this method and other two methods are 505, 363 and 373 respectively, which proves that the performance of this method is more outstanding than that of other two methods.