The proliferation of multi level cloud computing has ushered in unprecedented advancements in data storage and processing capabilities, yet it has simultaneously amplified the vulnerabilities associated with cybersecurity threats, prompting the need for robust protective measures. This literature review focuses on the multi-level intrusion detection and log management systems specifically designed for cloud environments, examining existing research that elucidates their architectures, functionalities, and effectiveness. By integrating multi-layered detection mechanisms spanning network, host, and application levels these systems offer comprehensive surveillance that significantly enhances the detection of anomalies and unauthorized access attempts in real-time.
Concurrently effective log management plays a pivotal role in the post-incident analysis and compliance auditing processes serving as a critical repository of historical data that significantly aids in identifying patterns of malicious behavior and facilitating comprehensive forensic investigations. By systematically collecting and organizing logs organizations can trace back through events to understand exactly what transpired during an incident. The review synthesizes various analytical frameworks and methodologies proposed in recent studies highlighting key advancements such as machine learning and artificial intelligence. These technologies not only optimize detection capabilities but also help to lessen false positive rates allowing security teams to focus on genuine threats rather than being overwhelmed by alarm fatigue. Ultimately robust log management is integral to enhancing overall security posture and ensuring regulatory compliance.
Furthermore, it scrutinizes the trade-offs inherent in the implementation of these systems, including computational overhead, privacy concerns, and the complexity of managing diverse cloud services, ultimately underscoring the necessity for a synergistic approach that harmonizes security with operational efficiency. By addressing these multifaceted challenges, this literature review aims to contribute to a deeper understanding of the essential features and best practices for multi-level intrusion detection and log management systems within the ever-evolving landscape of cloud computing.