Network Computer Virus Modeling And Analysis

While facilitates information disseminating,the Internet provides a breeding ground for the spread of computer viruses which threat the security of website.Computer viruses' self-replicate and spread are so strongly that they are turned to be the number one enemy of the Internet.As the transmission mechanism of computer viruses and biological viruses has many properties in common,experts and scholars use the dynamical modeling method of infectious diseases to study mechanism of computer viruses.In this dissertation,we study further the dynamical model with kill signals mechanism(SEIR-KS),in order to find the influence of user consciousness and bilinear propagation mechanism.Firstly,taking into account the user's self-prevention awareness of virus attacking,the user consciousness function is introduced into SEIR-KS.Thus,we proposed a modified SEIR model with both user consciousness and kill signals(U-SEIR-KS).We proved first that the solution of U-SEIR-KS is non-negative,and then investigated the stability of equilibrium.We showed theoretically that U-SEIR-KS have a stable virus-free equilibrium(pb ?,0,0,0)and a virus equilibrium(0.2752,0.0648,0.0377,0.5805).Secondly,observing the fact that the possible transmits target of viruses in SEIR-KS is not only I but also E,we introduce the bilinear infection rate into SEIR-KS which describe the transmitting strength of viruses to I and E.Thus,we proposed a modified SEIR mod el with both bilinear infection rate and kill signals(BL-SEIR-KS).We proved first that the solution of BL-SEIR-KS is non-negative,and then investigated the stability of equilibrium.We showed theoretically that U-SEIR-KS have a stable virus-free equilibrium(0.2667,0,0,0)and a virus equilibrium(0.4518,0.01963,0.01963,0.1516).Based on the theoretical analysis,we conduct numerical simulations on the above two new models.The work includes simulation of stability for equilibriums and simulation of comparison between the SEIR,SEIR-KS and new models,verify the validity of the new model.