Leveraging Intelligent Cloud Computing for Enterprise Data Engineering and Real-Time Adaptive AI Driven Cybersecurity Intelligence
DOI:
https://doi.org/10.15662/IJARCST.2024.0704018Keywords:
Intelligent Cloud Computing, Enterprise Data Engineering, Artificial Intelligence, Cybersecurity Intelligence, Machine Learning, Cloud Security, Real-Time Analytics, Adaptive Security, Data Pipeline Automation, Cloud-Native Architecture, Threat Detection, Big Data Analytics, Predictive Security, Enterprise Systems, Digital TransformationAbstract
The increasing complexity of enterprise digital ecosystems has created a critical need for intelligent cloud computing platforms capable of managing large-scale data engineering operations while providing adaptive cybersecurity protection. Modern organizations generate massive volumes of structured and unstructured data from business applications, IoT devices, digital platforms, and distributed computing environments. Traditional data processing and cybersecurity approaches often fail to address the speed, scale, and sophistication of contemporary technological challenges. Intelligent cloud computing integrates artificial intelligence, machine learning, automation, and advanced analytics to enhance enterprise data management and security intelligence. This research examines how cloud-based data engineering architectures combined with real-time adaptive AI-driven cybersecurity systems can improve organizational resilience, operational efficiency, and threat detection capabilities. The study explores the role of cloud-native technologies, automated data pipelines, machine learning algorithms, and intelligent security frameworks in developing self-adaptive enterprise environments. It investigates methods for integrating real-time analytics, anomaly detection, predictive modeling, and automated response mechanisms into cloud infrastructures. The research highlights challenges related to scalability, privacy, governance, model transparency, and cybersecurity complexity. A comprehensive methodology is proposed to evaluate intelligent cloud platforms through experimental analysis, performance measurement, and enterprise scenario simulations. The findings contribute toward the development of secure, intelligent, and scalable cloud ecosystems that support advanced data engineering and proactive cybersecurity management
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