An Insight into Machine Learning Techniques to Detect Anomalous Users

Anomalous user profile detection is a challenging problem in machine learning. Fake user accounts can be used for malicious activities and can cause extensive damage. This paper reviews the existing literature on user profile detection, categorizing the methods into supervised and unsupervised approaches. It also discusses the challenges and weaknesses of existing approaches and suggests possible areas for improvement. The paper provides a comprehensive overview and proposes a model to classify profiles as real or fake. Social media has made it easier for attackers to steal information and spread malicious content, which makes it important to detect and stop malicious profiles.