Natural language why-question in Business Intelligence applications: model and recommendation approach

Cloud technologies have several merits including the elimination of cost incurred when traditional technologies are adopted. Despite the benefits, the cloud is still facing security challenges thereby calling for cyber threat intelligence capable of identifying threats and providing possible solutions. However, dependence on traditional security mechanisms and approaches for security solutions within cloud environments presents challenges. This calls for cloud-native solutions which leverages cloud features for design and development of solutions for data and applications hosted and running within the cloud. Past studies have suggested the adoption of semantic technologies for cloud-based security mechanisms. However, the semantic processing of data faces challenges of data interconnectedness due to aggregation of data from diverse heterogenous sources. Hence, this study proposes a cloud-native architecture capable of connecting security-related data from different sources in the cloud to enhance cyber threat intelligence. It presents a proof-of-concept implementation of the proposed solution on Amazon AWS cloud, within an auto-scaling group for scalability and across multiple availability zones for high availability.