大数据背景下基于随机森林的非线性网络安全态势感知模型的建立

IF 2.4 Q2 ENGINEERING, MECHANICAL
Jinkui He, Weibin Su
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引用次数: 2

摘要

摘要为了探索大数据背景下基于随机森林的非线性网络安全态势感知模型的建立,提出了基于随机森林的多层次网络安全知识体系评价模型。本文提出了一个多层次的CSSA分析体系,并利用随机记忆算法建立了CSSA评价模型。提出了CSSA多层次分析框架,并利用随机森林算法建立了CSSA评价模型。对所有树木使用相同值的随机向量分布。在本文中,我们使用区间[0,1]来定量描述安全级别的权重。测试样本的训练样本比例为110:40,为了预测网络的安全性,预测的知识更接近真实值,预测多级安全的复杂性。使用不同寻常的森林。该树返回最受推荐的部分,这是对网络安全的更现实的评估。实验结果表明,考虑到网络安全情况,该方法的预测性能更接近实际值,性能优于其他两种方法。因此,使用随机存取存储器可以有效地预测多级安全情况的感知。事实证明,随机森林算法在网络安全方面具有更快、更高效的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishment of nonlinear network security situational awareness model based on random forest under the background of big data
Abstract In order to explore the establishment of a nonlinear network security situational awareness model based on random forest in the context of big data, a multi-level network security knowledge system evaluation model based on random forest is proposed. This article proposes a multi-level CSSA analysis system and then uses random memory algorithm to create a CSSA evaluation model. Also, it proposes a CSSA multi-level analysis framework and then uses random forest algorithm to build a CSSA evaluation model. A random vector distribution of the same values is used for all forest trees. In this article, the interval [0,1] is used to quantitatively describe the weight of the security level. The training sample ratio of test samples is 110:40, in order to predict the security of the network, the prediction of knowledge is closer to the true value, and the complexity of multi-level security is predicted. Use unusual forests. The tree returns the most recommended part, which is a more realistic assessment of network security. The experimental results show that considering the network security situation, the prediction performance of this method is closer to the actual value, and the performance is better than the other two methods. Therefore, perception of multi-level security situations can be effectively predicted using random access memory. It is proved that random forest is faster and more efficient in network security.
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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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