Graph database-based network security situation awareness data storage method

Graph database-based network security situation awareness data storage method
复制标题

基于图数据库的网络安全态势感知数据存储方法

DOI:
--
复制
发表时间:
2018
影响因子:
2.6
通讯作者:
Yong Wang
Yong Wang
中科院分区:
计算机科学4区
文献类型:
--
作者:
Xiaoling Tao;Yang Liu;Feng Zhao;Changsong Yang;Yong Wang

文献摘要

参考文献

被引文献

相似文献

随着互联网的快速发展,网络安全态势感知引起了人们的极大关注。在大规模复杂网络中,网络安全态势感知数据呈现出大规模、多源、异构的特点。近年来,人们对网络安全态势感知进行了大量的研究。然而,现有的方法大多以不同的方式存储不同类型的数据,这使得数据查询和分析效率低下。针对这一问题,提出了一种基于图数据库的层次化多域网络安全态势感知数据存储方法。在该方案中,我们建立了一个层次化的多域网络安全态势感知模型,将网络划分为不同的域,可以更有效地收集和处理感知数据。同时,为了统一我们的存储模式,我们还定义了基于图数据库的网络安全态势感知数据存储规则和方法。最后,在真实的数据集上的大量实验表明,与现有的存储模型相比,我们提出的方法是有效的。
With the rapid development of the Internet, network security situation awareness has attracted tremendous attention. In large-scale complex networks, network security situation awareness data presents the characteristics of large-scale, multi-source, and heterogeneous. Recently, much research work have been done on network security situation awareness. However, most of the existing methods store different types of data in different ways, which makes data query and analysis inefficient. To solve this problem, we propose a graph database-based hierarchical multi-domain network security situation awareness data storage method. In our scheme, we build a hierarchical multi-domain network security situation awareness model to divide the network into different domains, which can collect and dispose the awareness data more efficiently. Meanwhile, to unify our storage mode, we also define network security situation awareness data storage rules and methods based on graph database. Finally, extensive experiments on real datasets show that our proposed method is efficient compared to state-of-the-art storage models.
DOI: 10.1109/tnse.2018.2830307
发表时间: 2020-04-01
影响因子: 6.6
作者:
Cai, Zhipeng;Zheng, Xu
通讯作者: Zheng, Xu