Overview
This web page is for the NSF-RoRS-EAGER-HPC project, which is funded by the National Science Foundation (NSF) under Grant No. 2537355.
Award abstract:
This project aims to protect AI workloads, supercomputing cyberinfrastructure, and embargoed research
data from sophisticated threats. Our work has shown that these threats can be subtle, often disguised as
routine maintenance or accidental system failures, challenging security operators. Despite having subtle
traces, such attacks have a significant influence in disrupting research momentum, exfiltrating sensitive
data, corrupting scientific findings, and ultimately undermining public confidence in the AI innovation
engine. Traditionally, mitigating such evolving threats requires significant efforts to curate historical attack
traces and discover out-of-distribution lateral movements. By leveraging high-performance computing for
accelerated analytics, this project aims for a self-securing AI infrastructure protected by AI agents. Finally,
the project will rigorously educate scientists about insidious cyber-threats and mitigate risks associated with
collaborative AI in scientific research.
The team will focus on uncovering improper uses of resources in supercomputing cyberinfrastructure,
leveraging the National Center for Supercomputing Applications (NCSA) as the main vantage point. Our
technical approach involves deploying a federation of AI agents to process unstructured logs, including
high-speed interconnects, login hosts, and GPU nodes from a data lake such as AICyberLake. This pro-
vides statistical insights into utilization, job completion, energy consumption, temperatures, and graphs
of scientific workflow metadata using SLURM/PBS job schedulers. We will pinpoint uncertainties and
uncover new research security violations, including AI-driven malware and quantum-resistant cryptogra-
phy communications. The team will standardize a knowledge base of stealthy attack/abuse techniques on
GPU-accelerated systems, working with NIST, to provide a blueprint of such activities and corresponding
mitigations. Successful implementation will yield novel graph-based AI agents inference methods and pro-
vide concrete attack case studies. We will contribute to course materials on research security that will be
broadly applicable to other research computing centers, ultimately unleashing an AI innovation engine.
People
Role: Principal Investigator (PI)
Affiliation: National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign
Email: pcao3@illinois.edu
Ravishankar Iyer
Role: Co-Principal Investigator (Co-PI)
Affiliation: Coordinated Science Laboratory, University of Illinois at Urbana-Champaign
News and Events
Stay updated on the latest news and events related to the NSF-RoRS-EAGER-HPC project:
- September 1, 2025: Project officially begins!
- More news and events will be posted here soon.
Publications
A list of publications resulting from this project will be posted here as they become available. Please check back for updates.
This material is based upon work supported by the National Science Foundation under Grant No. 2537355
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Additional support for this project is provided by the National Center for Supercomputing Applications (NCSA) at the University of Illinois Urbana-Champaign.
