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.