Cyber Incident Classifications Using Ontology-Based Knowledge Representation for Cybersecurity Insurance in Financial Industry
Sam Adam Elnagdy, Meikang Qiu, Keke Gai · 2016
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.