The project goal is to create community infrastructure for collecting and using real world cybersecurity datasets. The datasets produced will support cybersecurity professionals in developing responses to emerging real world threats, help train students, be used in developing machine learning/AI applications, be utilized by researchers, and generally support development of a cybersecurity data corpus useful for multiple stakeholders.
Other Projects
IMR: MM-1A: Scalable Statistical Methodology for Performance Monitoring, Anomaly Identification and Mapping Network Accessibility from Active Measurements
The goal of this project is to develop new approaches…
The NSFNET Backbone Service
Operated and advanced one of the foundational high-speed research networks…
ATD: Collaborative Research: Extremal Dependence and Change-Point Detection Methods for High-Dimensional Data Streams with Applications to Network Cybersecurity
Developed advanced statistical methods to detect emerging cybersecurity threats and…