Abstract

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating AI into frameworks that ensure the security of sensitive data, otherwise, the ethicality of AI systems is compromised. This paper overviews compliance audits and their intricate relationship with cybersecurity frameworks CMMC and NIST 800-171, underscoring their complementary nature and shared objectives. Finally, the significance of AI in ensuring compliance with these frameworks will be explored, and the transformative potential of AI in automating processes and its advancements in risk management will be discussed.

Faculty Advisor/Mentor

Saltuk Karahan

Document Type

Paper

Disciplines

Artificial Intelligence and Robotics | Information Security | Risk Analysis

DOI

10.25776/p8c6-ag15

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The Transformative Integration of Artificial Intelligence with CMMC and NIST 800-171 For Advanced Risk Management and Compliance

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating AI into frameworks that ensure the security of sensitive data, otherwise, the ethicality of AI systems is compromised. This paper overviews compliance audits and their intricate relationship with cybersecurity frameworks CMMC and NIST 800-171, underscoring their complementary nature and shared objectives. Finally, the significance of AI in ensuring compliance with these frameworks will be explored, and the transformative potential of AI in automating processes and its advancements in risk management will be discussed.