计算机科学 ›› 2025, Vol. 52 ›› Issue (6A): 240600051-6.doi: 10.11896/jsjkx.240600051
夏卓群1, 周子豪1, 邓斌2, 康琛3
XIA Zhuoqun1, ZHOU Zihao1, DENG Bin2, KANG Chen3
摘要： 智慧水利是国家关键信息基础设施的重要行业和领域。网络安全态势评估技术的研究,为智慧水利的数据保护和网络安全建设提供了有力支撑。针对智慧水利网络模型特点以及基于单一D-S证据理论的网络安全态势评估模型中存在着主观依赖性、证据冲突大的问题,提出了一种基于改进D-S证据理论的智慧水利态势评估方法。首先,面对海量水利数据,使用深度自编码器对数据进行特征学习和过滤降维处理。然后,将处理后的数据交由深度神经网络进行二分类和多分类计算,并将结果融合,得出基本概率分配函数值,其将作为D-S证据理论的输入。最后,通过D-S证据理论的融合规则得到最终的网络安全态势评估结果。实验结果表明,相较于传统态势评估模型,所提方法能够在提升客观性的情况下,保持较高的准确性。
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