Yongpil Yoon

Papers

Total Citations

301

H-Index

About

Yongpil Yoon is a leading researcher at the intersection of cybersecurity, automotive systems, and cloud computing. His primary research areas include cyber-physical intrusion detection, deep learning for vehicle security, and computational offloading for resource-constrained environments. Yoon’s most significant contribution is his pioneering work on cloud-based cyber-physical intrusion detection for vehicles using deep learning, which has garnered 270 citations. In this influential study, he demonstrated that vehicles’ limited processing capabilities—a major barrier to advanced security—can be overcome by offloading computationally intensive intrusion detection tasks to the cloud. This paradigm shift enables real-time, deep learning-driven threat detection without compromising vehicle performance or energy efficiency. His related work on computation offloading for continuous intrusion detection workloads (31 citations) further refines this approach, optimizing for both energy efficiency and system performance. Yoon’s research has profound implications for the safety and security of connected and autonomous vehicles, offering a scalable solution to a critical vulnerability. His work is essential reading for students and researchers exploring the convergence of edge computing, cybersecurity, and intelligent transportation systems.