A healthy node selection method based on particle swarm optimization under network intrusion environment
Jun Zhang, Ping-ping Xia, Juan Zhang, Haiyun Peng · Proceedings of the ACM Turing Celebration Conference - China · 2019
In the network intrusion environment, how to realize the accurate selection of healthy nodes and use them for secure communication is a research hotspot of network security technology. In this paper, a healthy node selection method based on particle swarm optimization under the network intrusion environment is proposed. First, a fuzzy mathematical model is established for node features to constrain the cost of healthy node selection. Then, we introduce the particle swarm optimization algorithm and combine the uncertain factors to optimize the parameters to achieve the selection of healthy nodes. The experimental results show that, compared with the traditional BP neural network method, our healthy node selection method improves the accuracy of healthy node selection, shortens the running time, and can control the error after invasion to a reasonable range.