Next Generation AI Enabled Cognitive Platform for Secure Cloud Network Intelligence Self Healing Enterprise Systems and Data Driven Optimization
DOI:
https://doi.org/10.15662/IJARCST.2024.0706033Keywords:
Artificial Intelligence, Cloud Network Security, Cognitive Platform, Self-Healing Systems, Data-Driven Optimization, Machine Learning, Cybersecurity, Predictive Analytics, Intelligent Infrastructure, AutomationAbstract
The increasing complexity of cloud-based infrastructures and enterprise systems demands intelligent, adaptive, and autonomous solutions to ensure security, efficiency, and resilience. This paper presents a next-generation AI-enabled cognitive platform designed to enhance secure cloud network intelligence, enable self-healing enterprise systems, and support data-driven optimization. The proposed platform integrates artificial intelligence, machine learning, cognitive analytics, and automation into a unified framework capable of real-time monitoring, threat detection, and autonomous decision-making. By leveraging advanced data analytics and predictive modeling, the system can identify anomalies, anticipate failures, and implement corrective actions without human intervention. The concept of self-healing is central to the platform, allowing systems to diagnose and recover from faults dynamically. Additionally, the platform utilizes data-driven optimization techniques to improve resource allocation, performance efficiency, and operational agility. The architecture incorporates multi-layered security mechanisms and adaptive infrastructure components that evolve with changing environmental conditions and threat landscapes. While the benefits are significant, challenges such as data privacy, computational complexity, and integration issues remain. This research provides a comprehensive framework for building intelligent, secure, and resilient enterprise systems in modern cloud environments.
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