Machine Learning of Clues to New Cyberattacks from Honeypots and other Forensic Data

About this program

The Naval Postgraduate School, in collaboration with the National Academies of Science, Engineering, & Medicine, offers a fellowship focused on developing machine learning methods to detect new cyberattacks using honeypots and forensic data, particularly in cyber-physical systems. The research involves collecting network traffic data through deception techniques, applying machine learning algorithms, and exploring adversarial machine learning challenges. Eligibility is open to U.S. citizens, permanent residents, and postdoctoral and senior applicants, with stipends starting at $67,000 plus a $3,000 travel allotment, and higher stipends for experienced postdoctoral and senior associates.