From Conceptual Scaffold to Prototype: A Standardized Zonal Architecture for Wi-Fi Security Training

TL;DR

This paper proposes a standardized, modular Wi-Fi security training platform architecture and provides an open-source prototype to facilitate protocol-aware cybersecurity experimentation.

Contribution

It introduces a conceptual architecture for Wi-Fi-specific Cyber Ranges and delivers an open-source prototype demonstrating its core functionalities.

Findings

Designed a modular, scalable Wi-Fi-focused CR architecture

Developed an open-source prototype implementing scenario workflows

Provides a structured foundation for Wi-Fi security training environments

Abstract

Wi-Fi is the dominant wireless access technology, but its widespread use also exposes systems to threats such as rogue access points, deauthentication attacks, and other IEEE 802.11-specific vulnerabilities. Although Cyber Ranges (CRs) have become valuable platforms for cybersecurity training and experimentation, existing wireless-oriented solutions mainly target heterogeneous IoT or mobile-network settings, with Wi-Fi typically treated as one among many. As a result, dedicated CR environments for Wi-Fi-specific security experimentation remain limited. This gap is particularly relevant because wireless attacks often require protocol-aware experimentation that is difficult to reproduce in conventional training environments. This paper introduces a conceptual architecture for a Wi-Fi-focused CR tailored to IEEE 802.11 security scenarios and an open-source prototype. The proposed design is grounded in established CR design principles and organized around core infrastructure, learning management and support, monitoring, management, and access-control zones. Structuring the platform into these distinct zones, the architecture supports modularity, scalability, and future extensibility. Part of the design is realized in a prototype publicly available in a GitHub repository that implements the scenario generation, storage, retrieval, and instantiation workflow, offering an initial practical foundation for the proposed architecture. Overall, the paper provides a structured foundation for the future implementation of Wi-Fi-specialized CR platforms for targeted experimentation.