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American Journal of Applied Science and Technology

Peer Reviewed | Open Access | E-ISSN: 2771-2745
Published Article

Secure, Intelligent, and Distributed Communication Architectures for Autonomous Vehicular and Robotic Systems in V2X and 6G-Era Networks

Secure, Intelligent, and Distributed Communication Architectures for Autonomous Vehicular and Robotic Systems in V2X and 6G-Era Networks

Authors

  • Dilnoza Zubayd qizi Ismoilova
    Department of Electrical and Electronic Engineering, The University of Melbourne, Australia

Keywords:

Autonomous vehicles V2X communication real-time encryption federated learning

Abstract

The rapid convergence of autonomous systems, vehicular networks, edge intelligence, and next-generation wireless communication has fundamentally transformed the operational landscape of cyber-physical mobility ecosystems. Autonomous vehicles, cooperative robotic systems, and intelligent transportation infrastructures now rely on continuous, real-time exchange of high-volume sensor data across heterogeneous communication domains. This paradigm shift has intensified long-standing concerns related to security, privacy, latency, trust, and system resilience, particularly in Vehicle-to-Everything (V2X) environments where safety-critical decisions are made under strict temporal constraints. Against this backdrop, the present research undertakes an extensive theoretical and analytical investigation of secure communication architectures for autonomous vehicular and robotic systems, with a particular emphasis on real-time encryption, distributed intelligence, and emerging paradigms such as federated and split learning.

Building upon foundational work in secure real-time sensor data transmission for autonomous systems, recent scholarship has emphasized the necessity of encryption mechanisms that balance cryptographic robustness with computational feasibility and ultra-low latency requirements (Patil & Deshpande, 2025). However, encryption alone is insufficient in isolation. The integration of edge computing, collaborative learning frameworks, and heterogeneous V2X access technologies introduces new attack surfaces and systemic vulnerabilities that demand a holistic, multi-layered security perspective. This article synthesizes and critically evaluates existing research across vehicular networking, cybersecurity, distributed machine learning, and autonomous system safety standards, while advancing a unifying conceptual framework that aligns security mechanisms with functional safety, ethical governance, and scalability requirements in 5G- and 6G-enabled environments.

Methodologically, this study adopts a structured qualitative research design grounded in systematic literature analysis, conceptual modeling, and comparative theoretical evaluation. Rather than proposing a singular algorithmic solution, the research focuses on interpretive synthesis, identifying patterns, tensions, and gaps across diverse bodies of literature. The results articulate a set of interdependent security principles—real-time cryptographic adaptability, decentralized trust management, privacy-preserving intelligence, and lifecycle-aware system governance—that collectively define the requirements of future autonomous mobility ecosystems. The discussion extends these findings by engaging with scholarly debates on centralized versus distributed control, the trade-offs between transparency and privacy, and the implications of emerging 6G sensing and localization capabilities for security architectures.

By offering a comprehensive, theoretically grounded, and critically nuanced examination of secure communication in autonomous systems, this article contributes to the ongoing discourse on how intelligent mobility infrastructures can be designed to be not only efficient and scalable, but also trustworthy, resilient, and ethically aligned. The findings are intended to inform researchers, system architects, policymakers, and standards bodies engaged in shaping the next generation of autonomous and connected systems.

 

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