Year: 2025
Type: article
Abstract: The rise of social media has led to the proliferation of fake accounts, which are used for malicious activities such as spreading misinformation, phishing, fraud, and impersonation. These accounts can be automated (bots), human-operated, or hybrid, making their detection challenging. Various techniques, including machine learning, deep learning, and rule-based approaches, are employed to identify fake accounts. Detection methods analyze factors like user behavior, profile characteristics, activity patterns, and network connections. This paper explores the impact of fake social media accounts, the challenges in detecting them, and the effectiveness of different detection techniques in mitigating their risks. Keywords: Fake social media accounts, bot detection, misinformation, machine learning, deep learning, profile analysis, behavioral analysis, cyber threats, fraud detection, identity verification, social media security, automated accounts, spam detection, AI in cybersecurity. [1]
DOI: 10.55041/ijsrem44557
Authors: Mr. M. KARTHIKEYAN, Binaboina Venkatesh
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409412511