Kevin T. Kornegay received the B.S. degree in electrical engineering from Pratt Institute, Brooklyn, NY, in 1985 and the M.S. and Ph.D. degrees in electrical engineering from the University of California at Berkeley in 1990 and 1992, respectively. He is currently the IoT Security Professor and Director of the Cybersecurity Assurance and Policy (CAP) Center for Academic Excellence in the Electrical and Computer Engineering Department at Morgan State University in Baltimore, MD. His research interests include hardware assurance, reverse engineering, secure embedded systems, side‐channel analysis, and differential fault analysis. Dr. Kornegay serves on the technical program committees of several international conferences including the IEEE Symposium on Hardware Oriented Security and Trust (HOST), EEE Secure Development Conference (SECDEV), USENIX Security 2021, IEEE AIPR 2020: Trusted Computing, Privacy, and Securing Multimedia, the IEEE Physical Assurance and Inspection of Electronics (PAINE), and the ACM Great Lakes Symposium on VLSI (GLSVLSI). He is the recipient of numerous awards, including He is the recipient of multiple awards, including the NSF CAREER Award, IBM Faculty Partnership Award, National Semiconductor Faculty Development Award, and the General Motors Faculty Fellowship Award. He is currently a senior member of the IEEE and a member of Eta Kappa Nu and Tau Beta Pi engineering honor societies.
Recent curriculum vitae.
- K. T. Kornegay, W. L. Thompson, II, M. A, Reece, “An IoT Security Solution for Heterogeneous Networks,” IEEE MILCOM 2017, Restricted Access Program, Oct 23, 2017.
- H. Kasa, K. Kornegay, Y. Astake, M. Tienteu, “Secrecy Capacity and Energy Efficiency Evaluation of RLS – Kaiser Based Smart Antenna Systems,” 15th IEEE Int’l Conf. on Dependable, Automatic and Secure Computing (DASC 2017), pp. 675-680.
- D. Hamilton, L. Watkins, and K. Kornegay, “Autonomous Navigation Assurance with Explainable AI and Security Monitoring,” to appear in the Proceedings of the 2020 IEEE Applied Imagery Pattern Recognition.
- O. Toutsop, P. Harvey, and K. Kornegay, “Monitoring and Detection Time Optimization of Man in the Middle Attacks using Machine Learning,” to appear in the Proceedings of the 2020 IEEE Applied Imagery Pattern Recognition.
- Md.T. Arafin and K. Kornegay, “Autonomous Navigation under Adversarial Attack,” to appear in the Proceedings of the 2020 IEEE Applied Imagery Pattern Recognition.