Explainable AI in Sovereign Network Defense: A Systematic Review of Trustworthy Mechanisms for ISD-WAN Architectures

Abstract

The paradigm shift toward AI-driven autonomous network orchestration has precipitated a critical strategic vulnerability: the paradox of opaque autonomy. In mission-critical defense environments, the deployment of opaque models for intrusion detection and traffic management poses a severe risk to national security and decision-making accountability. This paper presents a systematic literature review (SLR) of eXplainable Artificial Intelligence (XAI) within the Intelligent and Secure SD-WAN (ISD-WAN) framework, adhering to the PRISMA 2020 guidelines. Through a rigorous analysis of thirty-two primary studies (2020-2026), we identified an architectural transition from post-hoc, management-plane explanations toward intrinsic, real-time interpretability within control and data planes. Our synthesis characterizes a fundamental trilemma between security enforcement, network performance, and computational overhead, highlighting the pivotal role of neuro-symbolic AI and blockchain as anchors for auditability and non-repudiation. We propose a multi-tiered interpretability roadmap thatAn analysis of the surveyed literature suggests a transition toward a multi-tiered interpretability roadmap, where the depth of the explanation is calibrated to the plane’s processing budget, whitch empowers sovereign entities to exercise verifiable control over autonomous information flows. By bridging the gap between algorithmic performance and strategic governance, this study establishes a structured survey and conceptual integration of emerging research framework for resilient, transparent, and technologically sovereign network infrastructures.