Powering Filtration Process of Cyber Security Ecosystem Using Knowledge Graph

Cyber Security breaches and attacks are on the ascendancy as corporations, governments, universities, and private individuals are conducting their business and personal transactions on the web. This increasing participating on the web necessitates that robust and efficient cyber security systems need to be put in place by these entities to safeguard their cyber assets. Intelligent Systems needs to be employed to buttress the cyber security protocols established in cloud computing for proper decision-making, which may depend on the effective knowledge representation. However, as one of the dominant industry standards for knowledge representation, Web Ontology Language (OWL) has limitations, such as the lack of support for custom relations. Pace University has extended OWL to support Knowledge Graph as a replacement to better support knowledge representation and decision making. This paper examines using KG as the basis in the design of a knowledge-representation system that drives the filtration process of a company's cyber security ecosystem in cloud computing by employing a use case of cyber security communications in-order to identify the entity relations of threat types for the filtration process.