Analysis of approaches for Real-time Threat Detection using Artificial Intelligence.

Abstract

This research is dedicated to scrutinizing the utilization of artificial intelligence techniques, specifically deep learning, to enhance the accuracy and efficiency of real-time cybersecurity threat detection. The aim is to explore the potential of harnessing advanced machine learning algorithms for the timely identification and classification of various cyber threats. Furthermore, this study seeks to assess the possible integration of this enhanced threat detection capability into an Information Security Risk Diagnosis System (ISRDS) to align with the objectives of the Project “Modelización de un sistema de riesgos de seguridad de la información (SDRSI) para su integración a sistemas de gestión de calidad” (Universidad Tecnológica Nacional – Facultad Regional Rosario, 2023) within the scope of this research. This endeavor aims to achieve more effective risk management and bolster organizations' stance on Information Security.