Future-Proofing National Cybersecurity: The Role of AI in Proactive Threat Hunting and Framework Optimization
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P104Keywords:
National Cybersecurity, AI in Cybersecurity, Proactive Threat Hunting, Cybersecurity Framework Optimization, Machine Learning for Threat Detection, Behavioral Analytics, Anomaly Detection, Cybersecurity Policy Development, Cybersecurity Frameworks (e.g., NIST CSF), Cybersecurity Governance, Digital Identity & Trust Frameworks, AI in Cybersecurity R&D, Cybersecurity in Emerging Technologies (e.g., IoT, 5G), AI in Cloud SecurityAbstract
The increasing complexity of cybersecurity threats poses significant challenges to national security, necessitating the adoption of advanced technologies. Artificial Intelligence (AI) has emerged as a critical tool in addressing these challenges through its ability to detect, respond to, and prevent cyber threats proactively. This paper explores the role of AI in enhancing national cybersecurity by focusing on two key areas: proactive threat hunting and compliance framework optimization. AI's ability to analyze vast datasets, detect anomalies, and predict potential attack vectors has significantly improved the speed and accuracy of threat detection. Furthermore, AI aids in automating compliance checks, identifying gaps in existing frameworks, and adapting to emerging regulatory standards. The findings highlight the potential of AI to future-proof cybersecurity by mitigating emerging threats such as AI-driven malware and adversarial attacks while enabling more dynamic and resilient compliance mechanisms. This work underscores the importance of integrating AI into national cybersecurity strategies to ensure long-term defence against evolving threats
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