This $242,024 Project Grant awarded by the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) to Carnegie Mellon University (CMU) focuses on improving the reliability and efficiency of machine learning (ML) models for detecting malicious software (malware). The project aims to develop new techniques to make ML-based malware detectors more resistant to being fooled by attackers, as well as more time- and space-efficient. Key innovations include novel approaches to combining multiple malware classifiers, new model architectures, and improved ML training methods tailored for the malware domain. The research results will be open-sourced where responsible, or otherwise distributed to verified anti-malware researchers and developers, to enable further advances in this critical security area. The project period spans May 2024 to April 2027.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $242.0k | 4/15/24 |