Enhancing Threat Detection and Mitigation Strategies in Cloud and Edge Computing Environments for Improved Cybersecurity and Network Resilience

Abstract

Cloud computing and edge computing have revolutionized the digital landscape by providing scalable, on-demand resources and enabling low-latency processing. However, the increasing reliance on these technologies has introduced new vulnerabilities and expanded the attack surface, creating significant challenges for cybersecurity and network resilience. This paper explores advanced threat detection and mitigation strategies to secure cloud and edge environments. It evaluates existing frameworks, identifies gaps, and proposes a hybrid model that combines machine learning-based anomaly detection with real-time threat response mechanisms. The research also highlights the importance of integrating security policies, enhancing encryption protocols, and implementing automated response systems to improve overall network resilience.