Account Takeover Prevention and Identity Verification with AI Models

Authors

  • Viraj Soni, Sumit Gupta

Keywords:

Account takeover, identity verification, artificial intelligence, fraud prevention, machine learning, biometric authentication, anomaly detection, cybersecurity

Abstract

Account Takeover (ATO) fraud has emerged as a critical cybersecurity threat, leading to significant financial and reputational losses for individuals and businesses. Traditional authentication mechanisms, including passwords and Multi-Factor Authentication (MFA), are increasingly vulnerable to sophisticated attacks such as credential stuffing, phishing, and social engineering. The rapid evolution of artificial intelligence (AI) has introduced advanced fraud detection and identity verification solutions that leverage machine learning, deep learning, and behavioral biometrics. This paper explores the threat landscape of ATO attacks, the role of AI in preventing such fraud, and emerging AI-driven authentication techniques. Furthermore, it evaluates the performance of AI-based security models, discusses regulatory and ethical considerations, and outlines future research directions in AI-powered fraud prevention.

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Published

30.10.2023

How to Cite

Viraj Soni. (2023). Account Takeover Prevention and Identity Verification with AI Models. International Journal of Intelligent Systems and Applications in Engineering, 11(11s), 632 –. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/7268

Issue

Vol. 11 No. 11s (2023)

Section

Research Article

License

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