UEBA patterns for Advanced Cyber Threat Prevention.

In this project proposal I am going to talk about the User Entity Behavior Patterns as a way to identify new and advanced threats, such as zero-day, insider threats, APTs and other attacks, where traditional signature-based detection systems are not as effective. A research question that this project is focusing on is “How user behavior entity patterns be used to enhance detection and prevention of advanced cyber threats, and how these methods compare to traditional cybersecurity measures?”
Some gaps related to UEBA can include ethical aspects related to user privacy, scalability issues and results related to false positive and negative outcomes.
The objective of this study is to assess the effectiveness of utilizing user behavior patterns in detecting and preventing advanced cyber threats utilizing deep learning and machine learning techniques.
The planned experimental methodology will involve collecting and analyzing data from various sources, including user interactions, login activities, system logs, and application usage patterns, the proposed approach aims to identify abnormal behaviors that could indicate the presence of malicious actors or compromised user accounts.