计算机科学 ›› 2022, Vol. 49 ›› Issue (7): 357-362.doi: 10.11896/jsjkx.210900103
• 信息安全 • 上一篇
赵冬梅1,2, 吴亚星1, 张红斌3
ZHAO Dong-mei1,2, WU Ya-xing1, ZHANG Hong-bin3
摘要: 针对复杂的网络安全态势预测问题,为了提高预测的收敛速度和预测精度,提出了一种基于改进粒子群优化双向长短期记忆(IPSO-BiLSTM)网络的网络安全态势预测模型。首先,针对所用数据集没有真实态势值的问题,采用了一种基于攻击影响的态势值计算方法,用于态势预测。其次,针对粒子群(PSO)算法易陷入局部最优值、搜索能力不均衡等问题,对惯性权重和加速因子进行改进,改进后的粒子群(IPSO)算法的全局和局部搜索能力平衡,收敛速度更快。最后,使用IPSO优化双向长短期记忆(BiLSTM)网络参数,提升预测能力。实验结果表明,IPSO-BiLSTM的拟合程度可达0.994 6,其拟合效果和收敛速度均优于其他模型。
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