Improved BP Algorithm Intrusion Detection Model based on KVM

With the development of cloud computing technology, the cost of commercial cloud resources is getting low, a malicious user could use the same cloud platform resources in a virtual machine to implement intrusion. For existing cloud Intrusion Detection System Only detect known attacks, the lower compatibility of different virtual network model. Based on the analysis of KVM network model, we propose the next cloud-based Intrusion Detection Model Based on Improved BP Algorithm. This model combines the PSO algorithm global optimization ability and BP algorithm gradient descent local search features, The PSO algorithm is introduced to optimize the value of the initial weight and threshold of BP into the momentum and adaptive learning rate method, so that BP faster network convergence, and effectively avoid the plunging in local optimum. Experimental results show that the model proposed by the average detection rate is higher, and is able to provide intrusion detection services for the cloud.