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Title	Blockchain-Ai Integration For Resilient Real-Time Cyber Security
ID_Doc	12575
Authors	Goundar S.
Year	2024
Published	Global Congress on Emerging Technologies, GCET 2024
DOI	http://dx.doi.org/10.1109/GCET64327.2024.10934609
Abstract	The rapid evolution of cyber threats, driven by artificial intelligence (AI) and machine learning (ML), has exposed critical gaps in traditional cybersecurity frameworks, particularly in real-time threat detection and response. This paper presents research on the Next-Gen Cyber Security Sentinel, a system that integrates AI algorithms with blockchain-based smart contracts to detect and mitigate sophisticated, AI-powered cyberattacks in real-time. Through the use of Software-Defined Networks (SDN), the system simulates complex attack scenarios, providing flexible and scalable network management. Penetration testing confirmed the system's ability to detect, respond to, and mitigate advanced cyber threats, ensuring enhanced protection of critical infrastructure. The findings were both novel and innovative, demonstrating that the integration of AI and blockchain technology significantly improves the speed and accuracy of real-time threat detection. This research contributes to the field of cybersecurity by offering a robust, scalable solution to counter emerging AI-driven attacks, particularly in critical sectors such as smart cities and Industry 4.0 environments. These findings offer crucial insights for advancing cybersecurity solutions in the face of rapidly evolving, AI-driven cyber threats. The AI-Blockchain platform achieved a 95% detection rate with a 2% false positive rate and maintained blockchain transaction latency under 200 milliseconds, demonstrating significant improvements in real-time threat detection and response capabilities. © 2024 IEEE.
Author Keywords	Artificial Intelligence; Blockchain; Cyber Security; Machine Learning; Penetration Testing; Real-time Security; Threat Detection

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