User Behavior Analysis for Detecting Compromised User Accounts: A Review Paper

Abstract

The rise of online transactions has led to a corresponding increase in online criminal activities. Account takeover attacks, in particular, are challenging to detect, and novel approaches utilize machine learning to identify compromised accounts. This paper aims to conduct a literature review on account takeover detection and user behavior analysis within the cybersecurity domain. By exploring these areas, the goal is to combat account takeovers and other fraudulent attempts effectively.

Keywords

• machine learning
• account takeover
• ato
• user behavior analysis
• literature review