Research On Virus Propagation Control Method Based On Node Adaptive Reconnection

With the rapid development of internet technology,information technology makes human life convenient,at the same time the widespread spread of computer network virus caused a great threat to network security,so control the virus transmission is imperative.How to suppress the spread of the virus has become a hot topic of concern to many scholars.In the past,most of the research on virus propagation is often based on the same network topology that the virus in the process of communication network topology remains unchanged,it does not conform to our real world in the actual situation of the network.Propagation and network topology should not be independent of the two processes,but mutual feedback,mutual influence,showing a abundant of dynamic behavior.In reality,when people learn that the spread of the virus in the crowd,will try to avoid contact with the sick people to adjust their behavior;computer virus spread similar to the prevalence of infectious diseases in the crowd,in the network when the node learns that there is an infected node in the neighbor,it will adapt to the avoidance behavior and disconnect from the infected node to contact the healthy node.We call this act as "disconnect for rewiring".The break-over of the nodes leads to the topology reconfiguration of the network,making the invariant network topology a dynamic network that changes at any time.And the dynamic network topology will affect the spread of the virus,so from the broken side to consider the dynamic network topology on the impact of virus transmission behavior more realistic.Based on the previous study of the random rewiring strategy and the node maximum degree of rewiring strategy,a rewiring strategy based on node degree and clustering coefficient is proposed.Simulation experiments show that this strategy can effectively control the virus propagation in complex networks.It is a important significance research.The main contents of this thesis are as follows:1.Research and analysis of cellular automata model.In the past,most scholars have studied the virus propagation process based on the differential equation method of mean field.The average field method can only reflect the average trend of virus transmission,and can not describe the individual difference of virus transmission process.In contrast,the cellular automata is a discrete dynamical system with a simple structure that can produce complex self-organizing behavior and can overcome the shortcomings of the mean field.2.According to the theory of cellular automata,a SIS virus propagation model based on complex network is established to describe the propagation behavior of nodes.Then,the two main factors influencing the propagation of complex network information-node degree and node clustering coefficient are proposed.We will name the new strategy DCC(degree-clustering-coefficient,DCC)strategy.3.Aiming at the rewiring strategy proposed in this thesis,the network,network and network model are used as the initial simulation network environment to analyze the behavior of computer virus in the process of breakage and rewiring.This includes the evolution of the virus,And the control method based on DCC strategy can significantly reduce the propagation speed and propagation scale of the virus in the network,and it is the best way to suppress the virus transmission compared with other control methods.In this thesis,the DCC strategy only needs to consider the local information of the network in the process of selecting the node,so the DCC-based control method is also applicable to the effective control of the virus transmission in the large-scale network.