NATURAL LANGUAGE QUERYING IN SIEM SYSTEMS: BRIDGING THE GAP BETWEEN SECURITY ANALYSTS AND COMPLEX DATA

Abstract

Incorporating NER in SIEM systems introduces a revolutionary approach to interacting with the data to security analysts. Security data, prearranged for using natural language to query, improves the systems' usability and accelerates decision-making and analysis of the security information. This paper concentrates on integrating NLP in SIEM systems and underlines the importance of bringing analysts closer to the masses of information. The literature part of this paper aims to review different emergency literature; furthermore, this paper presents the findings of simulations and real-life scenarios involving this technology and the strengths and weaknesses of this technology. If these challenges are combined, it can be noted that natural language querying can be used to enhance an organization's cybersecurity as intended.

Published Date: 20-05-2023