Self-Healing Cybersecurity System for Cloud Environments

Abstract

Cloud computing has become the backbone of today’s digital landscape. It provides high scalability, flexibility, and cost savings. However, its distributed and changing nature makes it susceptible to various cyber threats, such as insider misuse, ransomware, and advanced persistent threats (APTs). This paper introduces a Self-Healing Cybersecurity System (SHCS) for cloud environ- ments that merges intelligent anomaly detection with automatic recovery processes. The framework combines Machine Learning (ML) and Deep Learning (DL) models for real-time threat detection. These models quickly identify harmful activities and system issues in cloud environments. To ensure data integrity, blockchain technology logs information securely and transparently, aiding auditing and regulatory compliance. Experimental results show that this AI-driven method greatly improves system resilience, reduces operational downtime, and builds trust in multi-tenant cloud infrastructures.