Simulation Research on Computer Network Attack and Defense Model Based on Particle Swarm Optimization Algorithm

In the current computer network, relevant personnel can accurately find that there is a worm attack in the network system, and this kind of attack is a typical attack scheme in the computer network. In the process of exploring the computer network attack scheme, the appropriate virus propagation model is built by using its main characteristics. Based on PSO (Particle Swarm Optimization) algorithm, this paper studies the simulation of computer network attack and defense model. The research shows that among the three algorithms, the best value of DL (Deep Learning) is 10.73, the best value of AGA (Adaptive Genetic Algorithm) is 14.18, and the best value of this algorithm is 19.53. Similarly, in the comparison of average and worst value, the average and worst value of this algorithm are also due to the other two algorithms. It can be seen that the convergence accuracy and convergence speed of this algorithm are significantly higher than those of DL and AGA. Using the cryptographic mechanism under PSO algorithm, the probability of successful attack is calculated. Using the optimization and improvement of this kind of model to improve the running security of computer network.