AI-Enhanced Cybersecurity in Edge Computing: Threats, Solutions, and Future Directions

Edge Computing (EC) is revolutionizing applications ranging from smart cities to autonomous vehicles by enabling real-time data processing at the network edge. However, as EC continues to expand, it introduces significant cybersecurity challenges due to its decentralized architecture and resource constraints. This survey examines the primary security threats to EC systems and reviews defense frameworks proposed to mitigate these risks. In this article, we present a generic EC security architecture that evaluates 21 recently proposed research prototypes using multiple assessment criteria (i.e., those we have identified) across perception/monitoring, detection/protection, and defense functional layers. We analyze cybersecurity prototypes for EC through a structured qualitative and quantitative comparative analysis to highlight patterns using frequency distributions. Additionally, we identify key gaps in the current research, such as the need for scalable, efficient solutions and improved integration of heterogeneous devices. Finally, the survey provides insights into future research directions to strengthen edge computing security, offering valuable perspectives for researchers.