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A Method to Construct Vulnerability Knowledge Graph based on Heterogeneous Data

机译:一种基于异构数据构建漏洞知识图的方法

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In recent years, there are more and more attacks and exploitation aiming at network security vulnerabilities. It is effective for us to prevent criminals from exploiting vulnerabilities for attacks and help security analysts maintain equipment security that knows vulnerabilities and threats on time. With the knowledge graph, we can organize, manage, and utilize the massive information effectively in cyberspace. In this paper we construct the vulnerability ontology after analyzing multi-source heterogeneous databases. And the vulnerability knowledge graph is established. Experimental results show that the accuracy of entity recognition for extracting vendor names reaches 89.76%. The more rules used in entity recognition, the higher the accuracy and the lower the error rate.
机译:近年来,旨在越来越多的攻击和剥削旨在网络安全漏洞。我们有效地防止犯罪分子利用攻击漏洞,帮助安全分析师维护了解漏洞和威胁的设备安全性。通过知识图形,我们可以在网络空间中有效地组织,管理和利用大规模信息。在本文中,我们在分析多源异构数据库后构建漏洞本体。并且建立了漏洞知识图。实验结果表明,提取供应商名称的实体识别的准确性达到89.76%。实体识别中使用的规则越多,准确性越高,误差率越低。

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