Cybersecurity Challenges in Cloud-Edge Computing Convergence: A Systematic Analysis and Adaptive Defense Framework

Abstract

Cloud-edge convergence, integrating cloud scalability and edge real-time processing, has become the foundational architecture for latency-sensitive applications like autonomous driving and smart healthcare, while optimizing performance and cutting bandwidth costs. However, its distributed and heterogeneous nature brings unprecedented cybersecurity challenges beyond traditional centralized defense mechanisms. This study systematically analyzes cloud-edge vulnerabilities across four layers: edge nodes, communication, cloud-edge orchestration, and data lifecycle. By evaluating 135 2023–2025 peer-reviewed studies and real-world incident data, it assesses existing mitigation measures such as edge-native intrusion detection and secure orchestration protocols. An adaptive defense framework with dynamic risk assessment, multi-layered access control and collaborative threat intelligence sharing is proposed to meet cloud-edge constraints. The findings underscore the urgency of context-aware and cross-layer defense solutions, providing actionable insights for stakeholders and advancing cloud-edge security resilience.

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