White paper: A perspective on civilian-to-defence research transfer to SDD

2026-08-10

AI Summary

This study addresses a fundamental lifecycle mismatch between decade-long defense platform acquisition cycles and the rapid evolution of AI and software systems, which often require updates within hours or days. To resolve this tension, the paper proposes a “Software-Defined Defense” (SDD) framework that systematically adapts mature commercial practices—including DevOps, model-based systems engineering, and edge computing—to defense contexts. The SDD framework establishes a continuous, integrated loop spanning systems engineering, AI engineering, and connected infrastructure, enabling tactical, low-power edge execution, continuous compliance, variability management, and assured AI trustworthiness and sovereignty in contested environments. The work outlines short-, medium-, and long-term validation pathways and fosters collaboration among research, industry, policy, and defense organizations, leveraging existing capabilities from automotive, manufacturing, and aerospace sectors to advance SDD certification and deployment under operational conditions.

Abstract

Military capability is increasingly determined by software. Yet defence platforms are procured on decade-long timescales, while the software and AI models they carry must evolve in days or hours. This paper calls this mismatch the lifecycle paradox, and argues it is the central problem Software-Defined Defence (SDD) must solve. SDD rests on three dimensions: software and systems engineering (design, procurement, certification), AI engineering (sovereignty and trust of learned components), and connectivity and infrastructure engineering (timely exchange of information among sensors, AI, and operators). The proposed path to resilient SDD starts from civilian technologies, addressed through a continuous, DevOps-style loop: model-based systems engineering and simulation-based testing front-load design and verification; tactical connectivity and low-power edge execution carry that design into contested operation; continuous compliance, assurance, and variability management run as cross-cutting concerns. This loop is sustainable given capabilities already proven in automotive, manufacturing, space, and energy. The next step is validating them under adversarial or defence-certified conditions, with short-, medium-, and long-term paths to closing gaps. Closing the SDD gap while preserving civic benefits is a distributed responsibility: researchers must redirect methods toward adversarial conditions; industry must expose tooling to operational needs; policymakers must shape regulatory instruments; and defence agencies must validate results with operators. Recommendations span three horizons: a short-term baseline of adversarial testing and connectivity pilots; a medium-term pipeline of incremental certification; and a long-term validation closing the loop under operational conditions.

Problem

• lifecycle paradox
• Software-Defined Defence
• defense software
• AI model evolution
• procurement timescales

Innovation

• Software-Defined Defence
• lifecycle paradox
• DevOps-style loop
• model-based systems engineering
• adversarial testing