FPGA Hardware Accelerator for Real Time Security, CAEML Core Project 4A1
This project aims to develop a malware detector for detecting the latest ransomware attacks in real time. It will employ a combination of artificial intelligence and machine learning techniques to create a system that can both detect real-time ransomware attacks and help protect against future threats. The system will be tested using real-world data from NC State University and assessed for accuracy, precision, and recall. This project will provide a valuable resource to NC State and its users in defending against ransomware attacks.
University of Illinois - Urbana-Champaign
The grant—running from January 1, 2020 to July 31, 2023—is for a total of $123,728.
Paul D. Franzon
Build malware detector for detecting ransomware attacks in real time.