Abstract
Machine Learning Based System for Semantic Indexing Documents Related to Cybersecurity
Highlights
This article presents a semantic indexing software system which uses natural language processing (NLP) techniques to understand documents related to cybersecurity
We propose the use of a machine learning (ML) based NLP service and a domain ontology
In our study [8], we described in full detail the development of a domain ontology and of a ML based NLP model for cybersecurity
Summary
The dangers to cybersecurity are continually diversifying, and security specialists need to make constant efforts to be informed about the latest vulnerabilities, threats, types of attacks, software system protection solutions and so on. This paper proposes an automated system for semantic indexing of cybersecurity documents that can facilitate the access to information. The system components, techniques and technologies through which it can be implemented are described in detail. Up to this point, we implemented separately the most important components. Our study can be used as an example for developing semantic indexing solutions for other domains. The same technologies, architecture and components as those proposed above can be used. The main differences consist in the development of ontologies and ML based NLP models which have to be customized according to the characteristics of the chosen fields
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