A Comprehensive Survey of Intrusion Detection System Techniques in Cloud Environment

Abstract

The cloud delivers scalable, on-demand virtualized network resources, providing computing infrastructure, applications, and storage services through the internet. Securing the cloud is paramount to shield user data and infrastructure from malicious activities, necessitating the preservation of Confidentiality, Integrity, Availability, and the implementation of timely intrusion detection measures. The integral role of Intrusion Detection Systems (IDS) in monitoring and managing network traffic enhances the security of both user data and cloud services by detecting and preventing fraudulent activities. This study presents a holistic overview of existing security techniques, emphasizing their merits and limitations. It particularly delves into security concerns within each cloud service model, underscores the importance of feature selection and dimensionality reduction, and assesses the current state of IDS technology. IDS techniques are categorized based on their ability to identify attack types, placement, and configurations. Additionally, the study explores strategies like Virtual Machine Introspection (VMI) and Hypervisor Introspection (HVI). The study's structure centers on three main perspectives: cloud security concerns, the significance of feature selection, and a thorough analysis of existing IDS techniques. In conclusion, this work identifies prevalent security challenges and issues, while also highlighting potential areas for future research.”