Fake Social Media Accounts and Their Detection
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]
Authors
- B. Venkatesh
- M. Karthikeyan
Institutions
- Altair Engineering (United States) (US)
Publication Details
- Journal
- INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
- Published
- 2025-04-14
- DOI
- https://doi.org/10.55041/ijsrem44557
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00