Business
- Multidisciplinary University Research Initiative (MURI)
- Intellectual Property
- Small Business Opportunities
- Contracting
- Broad Agency Announcements
- Collaborative Alliances
- HBCU/MI Partnered Research Initiative
- Current CTAs
- Completed CTAs
- Current CRAs
- Cyber Security Research Alliance
- Distributed and Collaborative Intelligent Systems and Technology
- Multi-Scale Multidisciplinary Modeling of Electronic Materials
- Materials in Extreme Dynamic Environments
- Internet of Battlefield Things
- Scalable, Adaptive, and Resilient Autonomy (SARA)
- Strengthening Teamwork for Robust Operations in Novel Groups (STRONG)
- Tactical Behaviors for Autonomous Maneuver Collaborative Research Program (TBAM-CRP)
- Completed ITAs
- Partnership Methods and Opportunities
- Small Business
- Scientific Services Program
- Technology Transfer
- University Affiliated Research Centers (UARCs)
Objective

The overall objective of the Cyber Security CRA is to develop a fundamental understanding of cyber phenomena, including aspects of human attackers, cyber defenders, and end users, so that fundamental laws, theories, and theoretically grounded and empirically validated models can be applied to a broad range of Army domains, applications, and environments. ARL envisions the alliance bringing together government, industry and academia through this basic research program to develop and advance the state of the art of Cyber Security in the following areas:
- Learning for Deception Research Area seeks to develop theories and models that relate fundamental properties and capabilities of adaptive deception techniques for defense and mission resilience under dynamic cyber threats
- Detection Research Area seeks to develop theories and models that relate properties and capabilities of cyber threat detection and recognition processes/mechanisms to properties of a malicious activity, and of properties of Army networks.
- Agility Research Area seeks to develop theories and models to support planning and control of cyber maneuver (i.e., “maneuver” in the space of network characteristics and topologies) that would describe how control and end-state of the maneuver are influenced by fundamental properties of threats, such as might be rapidly inferred from limited observations of a new, recently observed threat.
Contact Information
ARL Collaborative Alliance Manager:
Dr. Michael Frame
michael.j.frame3.civ@army.mil
University Lead:
Professor Trent Jaeger
tjaeger@cse.psu.edu
Consortium Members
- Pennsylvania State University (lead)
- Carnegie Mellon University
- Indiana University
- The University of California at Davis
- The University of California Riverside
- Perspecta Labs