International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 6 Issue 6
November-December 2024
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Generative AI: Ransomware Attack Simulation and Workforce Education for IT Enterprises and Small Businesses
Author(s) | Mithilesh Ramaswamy |
---|---|
Country | USA |
Abstract | The rise of generative AI technologies has enabled a new generation of ransomware attacks that leverage voice spoofing, image and video manipulation, and realistic phishing schemes to exploit human vulnerabilities. These advancements allow attackers to craft highly convincing campaigns that deceive even cautious individuals, creating an urgent need for advanced defense mechanisms. This paper proposes a novel AI-driven ransomware attack simulation framework designed to educate and prepare the workforce against evolving threats. By simulating generative AI-enhanced attack scenarios, the system provides employees with hands-on training to recognize and respond to these sophisticated threats. Additionally, this paper emphasizes the importance of continuous learning, incorporating scenario-based exercises, and integrating threat awareness into organizational workflows. The proposed solution bridges the gap between evolving generative AI threats and workforce readiness, offering a path toward resilience in the face of advanced ransomware tactics. |
Keywords | Generative AI, ransomware simulation, workforce education, voice spoofing, image manipulation, phishing attacks, cybersecurity training, threat awareness |
Field | Computer Applications |
Published In | Volume 6, Issue 6, November-December 2024 |
Published On | 2024-12-19 |
Cite This | Generative AI: Ransomware Attack Simulation and Workforce Education for IT Enterprises and Small Businesses - Mithilesh Ramaswamy - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.26582 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i06.26582 |
Short DOI | https://doi.org/g8wkqh |
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E-ISSN 2582-2160
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