Project Grant 2403360

The University of South Carolina (USC) was awarded a $599,999 Project Grant by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to enhance network security through the implementation of a machine learning-based malware detection and classification system. The project aims to leverage programmable data plane (P4) switches and smart network interface cards (SmartNICs) to perform real-time deep packet inspection of Domain Name System (DNS) traffic and detect and classify malware such as Trojans, backdoors, and ransomware. Key objectives include developing malware detection applications for P4 switches and SmartNICs, implementing a control application to share threat intelligence and prevent malware propagation, and expanding the Ex-IoT platform to fingerprint and index detected malware. The funding will also support the dissemination of research outcomes through virtual lab libraries and tutorials. USC will collaborate with Louisiana State University (LSU) as a sub-grantee to deliver specific components of the project, including developing software applications, conducting research, and implementing machine learning algorithms.