基于朴素贝叶斯分类器的网络安全态势评估方法

发布时间：2018-03-22 01:36

本文选题：朴素贝叶斯　切入点：网络安全态势　出处：《计算机应用》2015年08期 　论文类型：期刊论文

【摘要】：针对目前网络安全态势评估范围局限、信息来源单一、时空复杂度较高且准确性偏差较大等问题,提出了一个朴素贝叶斯分类器的网络安全态势评估方法,充分考虑了多信息源与多层次异构信息融合,具有快速高效性,从整体动态上展示出网络当前安全状况,准确地反映了网络当前安全态势。最后利用网络实例数据,对所提出的朴素贝叶斯分类器的网络安全态势评估模型和算法进行了验证,实验结果表明了所提方法的正确性。
[Abstract]:Aiming at the problems of limited network security situation assessment scope, single information source, high space-time complexity and large accuracy deviation, a network security situation assessment method based on naive Bayesian classifier is proposed. Considering the fusion of multi-information source and multi-level heterogeneous information, it has fast and high efficiency. It shows the current security situation of the network dynamically and accurately reflects the current security situation of the network. Finally, the network instance data is used. The proposed network security situation assessment model and algorithm of naive Bayesian classifier are verified and the experimental results show that the proposed method is correct.
【作者单位】：湖南工业大学计算机与通信学院;
【基金】：国家自然科学基金资助项目(61073186)
【分类号】：TP393.08

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