Trusted AI-Driven Data Solutions for Enhanced Privacy in Military Support Networks

This proposal addresses the need for advanced, AI-enhanced privacy preservation architecture tailored to protect sensitive data within military family knowledge systems. Military families face distinct, evolving needs across health, social, and logistical domains, requiring robust, privacy-centric data management solutions. Our project aims to develop a secure knowledge base capable of integrating data from the Department of Defense (DoD), Veterans Affairs (VA), and social networks, offering military families support while maintaining the highest data integrity and confidentiality standards.In Phase I, the project will establish a modular reference architecture as a foundational structure for secure data handling and privacy management. This architecture will be designed to compartmentalize and anonymize sensitive information, allowing access based on a strict need-to-know basis. Key components will include dynamic access controls, AI-based anomaly detection, and real-time privacy compliance monitoring to support ongoing data security and resilience. To ensure effective and secure integration, the architecture will be grounded in open technology standards that facilitate adaptability across DoD systems.The feasibility of this privacy-preserving framework will be demonstrated through a use case co-developed with the Air Force District of Washington (AFDW), highlighting how information can be protected within a legacy military family knowledge base. This demonstration will outline how sensitive information can be shared across platforms while ensuring compliance with DoD privacy protocols and access control mandates. The project will further explore applications for a next-generation social network tailored to those who serve, enhancing connectedness and information access for military families.By the end of Phase I, our deliverables will include a comprehensive reference architecture with defined data interaction protocols, a validated AI-driven privacy compliance system, and an initial demonstration of the secure knowledge base for AFDW. This foundation will pave the way for a scalable Phase II prototype, with high potential for dual-use applications across government and commercial sectors. The solution aligns with DoD modernization priorities in Trusted AI, Autonomy, and Integrated Network Systems, setting a new standard for privacy-preserving data solutions in defense and civilian environments.