| Title | Security Situation Prediction based on Hybrid Rice Optimization Algorithm and Back Propagation Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Zhang, Xu, Ye, Zhiwei, Yan, Lingyu, Wang, Chunzhi, Wang, Ruoxi |
| Conference Name | 2018 IEEE 4th International Symposium on Wireless Systems within the International Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS) |
| Keywords | Backpropagation, backpropagation neural network, Biological neural networks, BP network security posture prediction method, BP Neural Network, Collaboration, Communication networks, Evolutionary algorithms, evolutionary computation, HRO, hybrid rice optimization algorithm, Metrics, network security situation awareness, neural nets, Neural Network Security, Neurons, optimisation, Optimization, policy-based governance, Prediction algorithms, pubcrawl, resilience, Resiliency, security, security of data, security situation prediction |
| Abstract | Research on network security situation awareness is currently a research hotspot in the field of network security. It is one of the easiest and most effective methods to use the BP neural network for security situation prediction. However, there are still some problems in BP neural network, such as slow convergence rate, easy to fall into local extremum, etc. On the other hand, some common used evolutionary algorithms, such as genetic algorithm (GA) and particle swarm optimization (PSO), easily fall into local optimum. Hybrid rice optimization algorithm is a newly proposed algorithm with strong search ability, so the method of this paper is proposed. This article describes in detail the use of BP network security posture prediction method. In the proposed method, HRO is used to train the connection weights of the BP network. Through the advantages of HRO global search and fast convergence, the future security situation of the network is predicted, and the accuracy of the situation prediction is effectively improved. |
| DOI | 10.1109/IDAACS-SWS.2018.8525625 |
| Citation Key | zhang_security_2018 |
Security Situation Prediction based on Hybrid Rice Optimization Algorithm and Back Propagation Neural Network