Survey of Fault Detection Recovery and Security Assurance in Cloud Computing Systems

Abstract

Cloud computing has become a fundamental computing paradigm that delivers scalable, flexible, and cost-effective services for modern applications. However, the increasing complexity of distributed cloud infrastructures has introduced significant challenges related to fault management, service reliability, and security assurance. This survey presents a comprehensive review of fault detection, recovery, and security assurance techniques employed in cloud computing systems. It examines various cloud fault categories, including crash, Byzantine, transient, permanent, hardware, network, and service-related faults, followed by recent fault detection approaches based on anomaly detection, machine learning, artificial intelligence, log analysis, predictive analytics, and continuous monitoring. The survey further review’s fault recovery and resilience mechanisms such as fault tolerance, replication, disaster recovery, self-healing, and cloud-native orchestration. In addition, it discusses security assurance techniques including access control, authentication, intrusion detection, and AI-driven risk management for protecting cloud environments against evolving cyber threats. A comparative analysis of recent studies highlights current research trends, major contributions, and existing challenges. The survey demonstrates that integrating intelligent fault detection, automated recovery strategies, and comprehensive security assurance significantly improves cloud reliability, availability, resilience, and operational efficiency, while identifying future research opportunities for developing autonomous, secure, and trustworthy cloud computing systems.