Cyber Collaborative Research Alliance

The Cyber Collaborative Research Alliance (PE 0601121A) is a basic research program within the Army's Research, Development, Test & Evaluation (RDT&E) budget. Its focus is on advancing the theoretical foundations of cyber science as applied to Army networks. The program is executed through a competitively selected consortium, known as the Cyber Security Collaborative Research Alliance (CSEC CRA), which brings together academia, industry, and government researchers. The goal is to develop fundamental laws, theories, and empirically validated models that can be applied across a broad range of Army domains, applications, and operational environments.

The primary objectives of the Cyber Collaborative Research Alliance center on three interrelated aspects of cyber security: understanding vulnerabilities and risks of Army networks to malicious activities, anticipating and analyzing such activities, and enabling agile cyber maneuver to thwart and defeat adversarial actions. The research employs a trans-disciplinary approach, explicitly considering the human element within cyber networks. This approach is designed to decrease the adversary's return on investment when targeting Army networks and to minimize any negative impact on network performance resulting from the implementation of cyber security measures.

Within the program, the main budget line item supports foundational research to create innovative theories, models, and methods for understanding, creating, predicting, and exploiting Windows of Superiority (WoS) in cyberspace. The aim is to achieve operational advantage for Multi-Domain Operations (MDO) by synchronizing and converging cyber capabilities across domains. Research efforts focus on identifying and formalizing key cyber attributes that predict WoS, developing methods for cyber resilience and deception, and mitigating adversarial deception, intrusions, and adversarial machine learning (AML) attacks.

For FY 2025, planned activities include research into methodologies for identifying, predicting, and exploiting cyber security Windows of Superiority, as well as exploring techniques for multidomain cyber deception in contested environments. The program will also investigate countermeasures against adversarial attacks and manipulation of machine learning algorithms used for network defense. Additionally, the impact of uncertainties and incomplete information on machine learning algorithms for cyber deception and network intrusion detection will be examined.

In FY 2026, the program will advance the theoretical foundation of multidomain deception in complex systems and adversarial environments, with a focus on tactical applications. Efforts will include developing measures of trustworthiness and robustness for complex systems, researching innovative machine learning techniques that minimize the need for continual retraining, and ensuring resilience against adversarial attacks. The program will also investigate approaches to support classifier training in simulated environments, aiming for efficient transfer to deployed environments with minimal labeled data from captured network packets.

The research conducted under this program is aligned with the Under Secretary of Defense for Research and Engineering's priority focus areas and supports the Army Modernization Strategy. The work is primarily performed by the Army Research Laboratory (ARL), leveraging its expertise in cyber science and network security. The program's framework is designed to integrate knowledge of cyber assets and adversary capabilities, providing dynamic defense mechanisms that adjust to changes in mission, asset vulnerability, and defense posture.

Budget adjustments for FY 2026 reflect a minor decrease due to economic factors, specifically a reduction in Advisory and Assistance Services to promote efficiencies and align with Executive Order 14222, which emphasizes government cost efficiency. No other program funding or acquisition strategies are specified for this line item, and the program continues to focus on basic research rather than procurement or direct acquisition activities.