Zero Trust-based Decentralized Identity Management System for Autonomous Vehicles

• URL: http://arxiv.org/abs/2509.25566v1
• Date: Mon, 29 Sep 2025 22:42:51 GMT
• Title: Zero Trust-based Decentralized Identity Management System for Autonomous Vehicles
• Authors: Amal Yousseef, Shalaka Satam, Banafsheh Saber Latibari, Mai Abdel-Malek, Soheil Salehi, Pratik Satam,
• Abstract summary: This paper presents a novel Zero Trust-based Decentralized Identity Management (D-IM) protocol for AVs.<n>By integrating the core principles of Zero Trust Architecture, "never trust, always verify", with the tamper resistant and decentralized nature of a blockchain network, our framework eliminates reliance on centralized authorities.<n>A comprehensive experimental evaluation, conducted across both urban and highway scenarios, validates the protocol's practicality.
• Score: 0.6131727058785479
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rise of autonomous vehicles (AVs) promises to significantly enhance transportation safety and efficiency by mitigating human error, which is responsible for over 90\% of road accidents. However, the increasing connectivity of AVs introduces new cybersecurity challenges, as traditional perimeter-based security models are inadequate for dynamic and untrusted environments. This paper presents a novel Zero Trust-based Decentralized Identity Management (D-IM) protocol for AVs. By integrating the core principles of Zero Trust Architecture, "never trust, always verify", with the tamper resistant and decentralized nature of a blockchain network, our framework eliminates reliance on centralized authorities and provides continuous verification for every entity. We detail the system's design, which leverages Hyperledger Iroha to enable lightweight and secure authentication without a central trusted entity. A comprehensive experimental evaluation, conducted across both urban and highway scenarios, validates the protocol's practicality. Our results demonstrate that the D-IM framework introduces minimal overhead, with less than 7.5\% reduction in Packet Reception Rate (PRR) in urban settings and an increase of under 11\% in Channel Busy Ratio (CBR) for LTE-V2X. These findings prove the protocol's efficiency and robustness, providing a resilient foundation for securing real-time V2X communication against impersonation and replay attacks.

Related papers

• Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks [77.17664010626726]
  We focus on the routing with multiple UAV clusters in low-altitude intelligent networks (LAINs)<n>To minimize the damage caused by potential threats, we present the zero-trust architecture with the software-defined perimeter and blockchain techniques.<n>We show that the proposed framework reduces the average E2E delay by 59% and improves the TSR by 29% on average compared to benchmarks.
  arXiv  Detail & Related papers  (2026-02-27T04:30:35Z)
• Scalable Hierarchical AI-Blockchain Framework for Real-Time Anomaly Detection in Large-Scale Autonomous Vehicle Networks [0.5505634045241287]
  Existing security schemes are unable to provide sub-10 ms anomaly detection and distributed coordination of large-scale networks of vehicles.<n>This paper introduces a three-tier hybrid security architecture HAVEN, which decouples real-time local threat detection and distributed coordination operations.<n>It incorporates a light ensemble anomaly detection model on the edge, Byzantine-fault-tolerant federated learning to aggregate threat intelligence at a regional scale, and selected blockchain mechanisms to ensure critical security coordination.
  arXiv  Detail & Related papers  (2025-11-16T15:30:46Z)
• Proactive DDoS Detection and Mitigation in Decentralized Software-Defined Networking via Port-Level Monitoring and Zero-Training Large Language Models [3.6260109722491465]
  Software-Defined Networking (cSDN) offers flexible and programmable control of networks but suffers from scalability and reliability issues.<n>Decentralized SDN (dSDN) Distributed alleviates these concerns by distributing control across multiple local controllers.<n>This architecture remains highly vulnerable to Denial-of-Service (DDoS) attacks.<n>We propose a novel detection and mitigation framework tailored for dSDN environments.
  arXiv  Detail & Related papers  (2025-11-01T08:57:29Z)
• When UAV Swarm Meets IRS: Collaborative Secure Communications in Low-altitude Wireless Networks [68.45202147860537]
  Low-altitude wireless networks (LAWNs) provide enhanced coverage, reliability, and throughput for diverse applications.<n>These networks face significant security vulnerabilities from both known and potential unknown eavesdroppers.<n>We propose a novel secure communication framework for LAWNs where the selected UAVs within a swarm function as a virtual antenna array.
  arXiv  Detail & Related papers  (2025-10-25T02:02:14Z)
• SkyTrust: Blockchain-Enhanced UAV Security for NTNs with Dynamic Trust and Energy-Aware Consensus [0.17188280334580194]
  Non-Terrestrial Networks (NTNs) based on Unmanned Aerial Vehicles (UAVs) are susceptible to security attacks due to their distributed and dynamic nature, which makes them vulnerable to rogue nodes.<n>In this paper, a new Dynamic Trust Score Adjustment Mechanism with Energy-Aware Consensus (DTSAM-EAC) is proposed to enhance security in UAV-based networks.
  arXiv  Detail & Related papers  (2025-08-26T07:08:34Z)
• Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things [61.43014629640404]
  Zero-Trust Foundation Models (ZTFMs) embed zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems.<n>ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversarial IoT environments.
  arXiv  Detail & Related papers  (2025-05-26T06:44:31Z)
• SafeAgent: Safeguarding LLM Agents via an Automated Risk Simulator [77.86600052899156]
  Large Language Model (LLM)-based agents are increasingly deployed in real-world applications.<n>We propose AutoSafe, the first framework that systematically enhances agent safety through fully automated synthetic data generation.<n>We show that AutoSafe boosts safety scores by 45% on average and achieves a 28.91% improvement on real-world tasks.
  arXiv  Detail & Related papers  (2025-05-23T10:56:06Z)
• Zero-Trust Mobility-Aware Authentication Framework for Secure Vehicular Fog Computing Networks [0.0]
  This paper presents a novel Zero-Trust Mobility-Aware Authentication Framework (ZTMAF) for secure communication in VFC networks.<n>The framework employs context-aware authentication with lightweight cryptographic primitives, a decentralized trust evaluation system, and fog node-assisted session validation to combat spoofing, replay, and impersonation attacks.
  arXiv  Detail & Related papers  (2025-05-21T17:03:39Z)
• CP-Guard+: A New Paradigm for Malicious Agent Detection and Defense in Collaborative Perception [53.088988929450494]
  Collaborative perception (CP) is a promising method for safe connected and autonomous driving.<n>We propose a new paradigm for malicious agent detection that effectively identifies malicious agents at the feature level.<n>We also develop a robust defense method called CP-Guard+, which enhances the margin between the representations of benign and malicious features.
  arXiv  Detail & Related papers  (2025-02-07T12:58:45Z)
• ACRIC: Securing Legacy Communication Networks via Authenticated Cyclic Redundancy Integrity Check [98.34702864029796]
  Recent security incidents in safety-critical industries exposed how the lack of proper message authentication enables attackers to inject malicious commands or alter system behavior.<n>These shortcomings have prompted new regulations that emphasize the pressing need to strengthen cybersecurity.<n>We introduce ACRIC, a message authentication solution to secure legacy industrial communications.
  arXiv  Detail & Related papers  (2024-11-21T18:26:05Z)
• A Prototype Model of Zero-Trust Architecture Blockchain with EigenTrust-Based Practical Byzantine Fault Tolerance Protocol to Manage Decentralized Clinical Trials [5.565144088361576]
  This paper proposes a prototype model of the Zero-Trust Architecture (z-TAB) to integrate patient-generated clinical trial data during DCT operation management. The Internet of Things (IoT) has been integrated to streamline data processing among stakeholders within the blockchain platforms.
  arXiv  Detail & Related papers  (2024-08-29T20:18:00Z)
• Towards Secure and Private AI: A Framework for Decentralized Inference [14.526663289437584]
  Large multimodal foundational models present challenges in scalability, reliability, and potential misuse.<n>Decentralized systems offer a solution by distributing workload and mitigating central points of failure.<n>We address these challenges with a comprehensive framework designed for responsible AI development.
  arXiv  Detail & Related papers  (2024-07-28T05:09:17Z)
• A Zero Trust Framework for Realization and Defense Against Generative AI Attacks in Power Grid [62.91192307098067]
  This paper proposes a novel zero trust framework for a power grid supply chain (PGSC) It facilitates early detection of potential GenAI-driven attack vectors, assessment of tail risk-based stability measures, and mitigation of such threats. Experimental results show that the proposed zero trust framework achieves an accuracy of 95.7% on attack vector generation, a risk measure of 9.61% for a 95% stable PGSC, and a 99% confidence in defense against GenAI-driven attack.
  arXiv  Detail & Related papers  (2024-03-11T02:47:21Z)
• A Survey and Comparative Analysis of Security Properties of CAN Authentication Protocols [92.81385447582882]
  The Controller Area Network (CAN) bus leaves in-vehicle communications inherently non-secure. This paper reviews and compares the 15 most prominent authentication protocols for the CAN bus. We evaluate protocols based on essential operational criteria that contribute to ease of implementation.
  arXiv  Detail & Related papers  (2024-01-19T14:52:04Z)
• Smart and Secure CAV Networks Empowered by AI-Enabled Blockchain: Next Frontier for Intelligent Safe-Driving Assessment [17.926728975133113]
  Securing a safe-driving circumstance for connected and autonomous vehicles (CAVs) continues to be a widespread concern. We propose a novel framework of algorithm-enabled intElligent Safe-driving assessmenT (BEST) to offer a smart and reliable approach.
  arXiv  Detail & Related papers  (2021-04-09T19:08:34Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.