The AI Shield and Red AI Framework: Machine Learning Solutions for Cyber Threat Intelligence(CTI)
Simran, Sonu Kumar, Aarti Hans · 2024
Cybersecurity is rapidly evolving, with machine learning and artificial intelligence (AI) playing increasingly vital roles in bolstering threat detection, response, and proactive defense. Two prominent solutions, the AI Shield and Red AI frameworks, utilize machine learning to address Cyber Threat Intelligence (CTI) challenges. While AI Shield focuses on real-time monitoring and threat intelligence, Red AI employs a dedicated AI Red Team to simulate adversaries and conduct technical attacks on AI systems. Both frameworks enhance organizations' abilities to detect and respond to cyber threats proactively. However, integrating AI into cybersecurity presents challenges such as AI failures, continuous updates, and the lack of explainability. Despite these challenges, ongoing AI research will lead to the adoption of new technologies to enhance protection and safety, while threat actors continue to develop new attack capabilities. Integrating CTI into Security Operations Centers (SOCs) enhances cybersecurity by improving situational awareness, detection, prevention, response, and proactive defense. However, challenges like data overload, skills, and collaboration can hinder CTI integration into SOC operations. Overall, the AI Shield and Red AI frameworks, along with CTI integration into SOC operations, offer promising solutions for enhancing cybersecurity against evolving threats.