International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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The Rise of AI-powered Cybercrime: a Data-driven Analysis of Emerging Threats

Author(s) Poli Reddy Reddem
Country United States
Abstract The integration of artificial intelligence (AI) in cybercrime represents a transformative shift in the global threat landscape, introducing unprecedented challenges to cybersecurity frameworks. This comprehensive article examines the dramatic 238% surge in AI-powered cyber attacks during 2023, resulting in global damages exceeding $8.5 billion. Through analysis of 100,000 malware samples, 50,000 documented incidents, and 2,500 attack patterns across Fortune 500 companies, this study quantifies the impact of AI integration in cyber attacks. Key findings reveal that AI-enhanced attacks achieve a 67% higher success rate while reducing operational complexity by 72%. The article demonstrates concerning trends across four critical domains: automated attacks, AI-enhanced phishing (showing an evolution from 2.9% to 8.7% success rate), malware evolution, and deepfake-based fraud. The article also presents actionable mitigation strategies, including AI-based security solutions that demonstrate a 97.8% improvement in response efficiency, reducing incident response times from 6 hours to 8 minutes. This article provides a framework for organizations to strengthen their security posture against emerging AI-powered threats through systematic implementation of advanced defense mechanisms and strategic investment in AI-enhanced security solutions.
Keywords AI-Powered Cybercrime, Machine Learning Security, Advanced Threat Detection, Cybersecurity Analytics, AI Security Implementation
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-11-18
Cite This The Rise of AI-powered Cybercrime: a Data-driven Analysis of Emerging Threats - Poli Reddy Reddem - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.30744
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.30744
Short DOI https://doi.org/g8rdz2
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