Securing Data Engineering Pipelines in Cloud Environments Through Ai-Powered Intrusion Detection and Quality Assurance

With Cloud computing, data storage and processing have improved consideration to the ability to scale and use services whenever needed. Still, the fact that networks are flexible introduces serious difficulties when trying to address and stop complex cyber threats. The paper offers a new strategy for boosting data security in the cloud world by applying Cognitive Intrusion Detection Systems (CIDS). In contrast to main IDS solutions, CIDS keep exploring and finding novel threats through artificial intelligence, machine learning, and being alert to their context. The suggested way uses models based on knowledge with pattern recognition and anomaly detectors to identify malicious activities in networks. Tests on significant datasets in the cloud prove that AI systems are better at detecting threats, lead to fewer false alarms, and respond well to shifting threats. According to the findings, CIDS has the potential to help with smart management of security in today's cloud environments.