CAJ | 학술논문

为了有效地预测网络安全态势，在态势因子和灰色理论的基础上，提出了将灰色GM(1,1)和GM（1,N）模型相结合来预测网络安全态势的方法。首先筛选态势因子，再利用模型GM(1,1)对态势因子的变化进行预测，得到N个态势因子变化函数，最后利用这些函数和模型GM(1, N)对网络安全态势进行预测。将灰色GM(1,1)模型、神经网络模型和本文方法对网络安全态势进行预测，实验结果表明，本方法能够更准确地预测网络安全态势。
위료유효지예측망락안전태세，재태세인자화회색이론적기출상，제출료장회색GM(1,1)화GM（1,N）모형상결합래예측망락안전태세적방법。수선사선태세인자，재이용모형GM(1,1)대태세인자적변화진행예측，득도N개태세인자변화함수，최후이용저사함수화모형GM(1, N)대망락안전태세진행예측。장회색GM(1,1)모형、신경망락모형화본문방법대망락안전태세진행예측，실험결과표명，본방법능구경준학지예측망락안전태세。
In order to forecast network security situation effectively, puts forward a forecast method which combines GM(1,1) and GM(1,N) model on the basis of situation factors and grey theory. First filters situation factors, then applies model GM(1,1) to forecast variation of the situation factors, and obtainsN functions of situation factors variation, finally uses the functions and grey model GM(1,N) to forecast network security situation. The grey model GM(1,1), neural network model and the proposed method are used to forecasts network security situation, and the experimental results prove that the proposed method forecasts more accurately the network security situation.