From Cyber Frameworks to Autonomous Defense: A U.S.-Centric Model for AI-Integrated Compliance
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V4I1P109Keywords:
U.S. Cybersecurity Frameworks, AI-Integrated Compliance, Autonomous Cyber Defense, NIST Cybersecurity Framework (CSF), AI-Driven Threat Detection, Reinforcement Learning in Cybersecurity, AI Risk Assessment, Data Privacy Regulations, Cybersecurity in Emerging Technologies (e.g., IoT, 5G), AI in Cloud Security, Autonomous Cyber Defense SystemsAbstract
The rapid integration of artificial intelligence (AI) into cybersecurity frameworks is transforming the landscape of compliance and defense mechanisms across public and private sectors. Traditional compliance frameworks, such as the National Institute of Standards and Technology (NIST) Cybersecurity Framework and Cybersecurity Maturity Model Certification (CMMC), often lack the agility and scalability required to address modern cyber threats effectively. This study explores an innovative U.S.-centric AI-integrated compliance model that incorporates advanced AI techniques such as machine learning (ML), natural language processing (NLP), and autonomous response systems. By automating compliance monitoring and enabling proactive cybersecurity measures, the proposed model bridges the gap between static frameworks and dynamic defense systems. Challenges such as algorithmic bias, regulatory hurdles, and technical constraints are also addressed, alongside policy recommendations for fostering AI innovation. The findings underscore the transformative potential of autonomous AI-enabled compliance and defense mechanisms in mitigating risks, enhancing efficiency, and ensuring scalable implementation across diverse sectors
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