基于本体知识表示的金融网络安全保险网络事件分类

S. Elnagdy, Meikang Qiu, Keke Gai
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引用次数: 25

摘要

网络安全保险作为一个新兴行业,发展迅猛,主要服务于金融行业,帮助金融企业降低网络安全风险。了解风险分类是运营网络安全保险的一个重要方面。然而,当服务系统规模变大时,分类表示将变得复杂。风险表述不当可能导致财务损失或操作失误。本文解决了这一问题,并提出了一种基于本体的网络安全保险知识表示方法。该方法采用语义技术衍生的知识表示,称为语义网络事件分类(SCIC)模型。我们的方法是专门针对网络安全保险领域设计的,这已经通过我们的实验进行了评估。
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Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry
As a recent emerging industry, cybersecurity insurance has been growing ambitiously fast, which mainly serves the financial industry and assists financial firms to reduce cybersecurity risks. Understanding the risk classification is an important hemisphere for operating cybersecurity insurance. However, the classification representation will be complicated when the service system becomes large. Improper presentation of the risks can result in financial loss or operational mistakes. This paper addresses this concern and proposes an approach using ontology-based knowledge representation for cybersecurity insurance. The approach is named as Semantic Cyber Incident Classification (SCIC) model, which uses knowledge representation deriving from semantic techniques. Our approach is specifically designed for targeting at cybersecurity insurance domain, which has been assessed by our experiments.
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