IEEE Transactions on Services Computing

Semantically Rich Framework to Automate Cyber Insurance Services

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With the rapid enhancements in technology and the adoption of web services, there has been a significant increase in cyber threats faced by organizations in cyberspace. It has become essential to get financial cover to mitigate the expenses due to a security incident. Organizations want to purchase adequate cyber insurance to safeguard against the third-party services they use. However, cyber insurance policies describe their coverages and exclusions using legal jargon that can be difficult to comprehend. Parsing these policy documents and extracting the rules embedded in them is currently a very manual time-consuming process. We have developed a novel framework that automatically extracts the coverage and exclusion key terms and rules embedded in a cyber policy. We have built our framework using Information Retrieval and Artificial Intelligence techniques, specifically Semantic Web and Modal Logic. We have also developed a web interface where users can find the best matching cyber insurance policy based on particular coverage criteria. To validate our approach, we used industry standards proposed by the Federal Trade Commission document (FTC) and have applied them against publicly available policies of seven insurance providers. Our system will allow cyber insurance seekers to explore various policy documents and compare the paradigms mentioned in those documents while selecting the best relevant policy documents.

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artificial intelligence, cyber insurance, cybersecurity, knowledge graph, knowledge representation, ontology, policies.




doi: 10.1109/TSC.2021.3113272.

Downloads: 478 downloads

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