International Journal on Science and Technology

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AI and Machine Learning in Account Takeover Fraud Detection: Challenges and Mitigation Strategies

Author(s) Prabhavathi Matta
Country United States
Abstract Account takeover fraud represents a significant threat to online security, leading to financial losses and reputational damage for both individuals and organizations. As cyber threats become increasingly sophisticated, traditional security measures have proven insufficient in combating these sophisticated attacks and using Artificial Intelligence (AI) in fraud detection has gained prominence. AI systems can analyze vast amounts of data to identify patterns and anomalies indicative of fraudulent activities. However, these systems are not without challenges.This paper explores how Artificial Intelligence (AI) and Machine Learning (ML) address these challenges by leveraging advanced analytics to detect anomalies and predict fraudulent activities. While AI-driven systems significantly enhance detection capabilities, they also present challenges such as false positives, data dependency, and ethical concerns. This study offers a comprehensive exploration of AI’s role in fraud detection, mitigation strategies, and emerging trends shaping the future of account security.
Keywords CyberSecurity, Account Takeover, Digital Fraud Detection,Machine Learning, Technology Modernization, Digital Transformation, Information Security, Multi-Factor Authentication (MFA), Threat Intelligence, Data Protection, Encryption, Continuous Monitoring, Identity Verification
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 15, Issue 2, April-June 2024
Published On 2024-05-02
Cite This AI and Machine Learning in Account Takeover Fraud Detection: Challenges and Mitigation Strategies - Prabhavathi Matta - IJSAT Volume 15, Issue 2, April-June 2024. DOI 10.71097/IJSAT.v15.i2.1134
DOI https://doi.org/10.71097/IJSAT.v15.i2.1134
Short DOI https://doi.org/g8z8k3
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