AI-Enhanced SOC Operations: Real-Time Compliance and Threat Management for the U.S. Defense Sector
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V5I2P109Keywords:
Artificial Intelligence (AI), Security Operations Center (SOC), Automation in Cybersecurity, Machine Learning (ML), Security Orchestration, Automation, and Response (SOAR), Threat Detection and Response, Regulatory Compliance, Cybersecurity Posture ManagementAbstract
The evolving cybersecurity landscape within the U.S. defense sector presents an unprecedented challenge, requiring swift adaptation to mitigate sophisticated threats. Traditional Security Operations Centers (SOCs) often struggle to manage real-time compliance with defense-specific regulations and respond effectively to advanced persistent threats (APTs). Artificial Intelligence (AI) has emerged as a pivotal enabler, offering enhanced capabilities for threat detection, automated incident response, and compliance management. This paper explores the transformative role of AI in SOC operations, emphasizing real-time compliance and threat management tailored for the defense sector. By leveraging machine learning, natural language processing, and advanced analytics, AI-driven SOCs demonstrate improved operational efficiency, reduced false positives, and compliance automation. The discussion includes a review of state-of-the-art AI tools, integration frameworks, and real-world applications, along with the technical and ethical challenges of implementation. The findings underscore AI's critical role in enhancing cybersecurity resilience for the U.S. defense sector
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