CCRI: Planning-C: A Community Research Infrastructure for Integrated AI-Enabled Malware and Network Data Analytics

The severity, frequency, scope, and sophistication of cybercrimes and cyberattacks have exploded in recent years, which resulted in huge financial damages to organizations, and threatened the critical infrastructures (e.g., energy grid, water safety, transportation, health care) and the most basic foundation of our society. While a host of open-source technologies for cybersecurity and for artificial intelligence have been developed and used by researchers in each community; research opportunities that leverage both of these technologies to tackle problems at the intersection of cybersecurity and artificial intelligence are not broadly accessible to cybersecurity community and AI community due to challenges, such as protection of sensitive information in network data, limited ground truth data, zero-day vulnerabilities, evasive malware, and processing voluminous and high-dimensional network data.

This Planning-C project, conducted in collaboration between Pennsylvania State University, Merit Network, and University of Texas at Arlington, aims to broadly solicit inputs from the cyber security and AI research communities regarding (1) research opportunities of cybersecurity that can be addressed using artificial intelligence, and (2) associated infrastructures needs that are not broadly available to the research communities. A tangle output of the planning workshop is to generate and publish a report in a suitable venue.

The outcome of this planning project will identify critical cybersecurity problems that can benefit from AI-enabled solutions as well as infrastructure requirements for these AI-enabled cyber security research that are not broadly accessible to the cybersecurity community and the AI community.

The identification of these research opportunities and infrastructure needs at the intersection of cybersecurity and artificial intelligence will expedite the selection, integration, and adaptation of relevant open-source software tools and infrastructures, as well as the creation of new tools, as needed. These tools and infrastructures will not only accelerate the critically needed advancement of cyber security solutions using AI, but also broaden the participation of early career scholars and students from under-represented groups in STEM in these research opportunities to further enhance the diversity of next-generation cybersecurity and AI workforce.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.