Abstract
In this paper, we have proposed the design of a Security Information Management Ontology (SIMOnto) framework, which utilizes natural language processing and statistical analysis to mine an exhaustive list of concepts and their relationships in an automatic way. Concepts are extracted using TF-IDF and LSA techniques whereas, relations between them are mined using semantic and co-occurrence based analyses. The mined concepts and relations are presented to domain experts for validation before creation of ontology using Protege.