Junfeng Sun1, Chenghai Li1, Yafei Song1,*, Peng Ni2, Jian Wang1
Computer Systems Science and Engineering, Vol.47, No.1, pp. 993-1021, 2023, DOI:10.32604/csse.2023.039215
Abstract The accuracy of historical situation values is required for traditional network security situation prediction (NSSP). There are discrepancies in the correlation and weighting of the various network security elements. To solve these problems, a combined prediction model based on the temporal convolution attention network (TCAN) and bi-directional gate recurrent unit (BiGRU) network is proposed, which is optimized by singular spectrum analysis (SSA) and improved quantum particle swarm optimization algorithm (IQPSO). This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data. Furthermore, a prediction model of TCAN-BiGRU… More >
Login
Register
