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May 7, 2026Journal of King Saud University - Computer and Information Sciences0 citationsOpen Access

Federated-trust sharded blockchain for real-time forensics and secure data collaboration in cooperative V2X

YZYongming ZhangCLChaoyue LiLLLei Liu

Key Points

  • The study aims to develop a federated-trust sharded blockchain to ensure secure, real-time data sharing and forensics in cooperative V2X environments.
  • Proposed a federated trust oracle integrating GNSS, OBD, IMU, and RSU observations.
  • Developed a hybrid cross-shard commit protocol with adaptive finality for secure collaboration.
  • Conducted large-topology emulation and hardware-in-the-loop testing to validate the framework.
  • Achieved sub-second forensic anchoring and cross-shard finality below 1.2 seconds.
  • Improved effective throughput by up to 35%, with 1.6-2.3 times higher TPS than the HotStuff baseline.
  • Reduced rollback rate and per-event bandwidth by up to 40% and 25%, respectively.

Abstract

Cooperative V2X is evolving toward city-scale deployment, yet current infrastructures still lack a network substrate that jointly provides cross-domain trust, low-latency finality, and privacy-preserving, auditable evidence for safety-critical decisions. This paper proposes a federated-trust sharded blockchain that turns heterogeneous vehicular and roadside measurements into accountable records and enables real-time forensic collaboration and secure data sharing across operators and city management authorities. A federated trust oracle fuses GNSS, OBD, IMU, RSU observations, and device attestations into uncertainty-aware scores that steer committee election, voting weights, and traffic shaping in each shard. On this basis, we design a hybrid cross-shard commit protocol with adaptive finality, combining atomic channels for forensic-critical transactions and optimistic channels for routine collaboration, and we establish safety/liveness conditions and provide proof sketches under the stated partial-synchrony assumptions and bounded collusion. For the forensic layer, a two-stage pipeline anchors minimal sufficient evidence with sub-second local finality, while editable proofs built on traffic-aware extended Merkle trees and zero-knowledge attestations support publicly verifiable, legally compliant edits with O (n) verification overhead. An SLA-aware, learning-assisted scheduler adapts committee size, batching, and cross-shard parallelism to dynamic traffic and attack patterns so as to meet latency, throughput, and rollback targets. Large-topology containerized emulation on a dedicated workstation, complemented by a small hardware-in-the-loop testbed, shows that the proposed framework achieves sub-second forensic anchoring and 95th-percentile cross-shard finality below 1. 2 s. Across the representative baselines used in this study, it improves effective throughput by up to 35\%; in particular, at comparable L₏₉₅, it achieves 1. 6–2. 3 higher TPS than the single-chain HotStuff baseline under the tested emulation conditions, while reducing rollback rate and per-event bandwidth by up to 40\% and 25\%, respectively. These results indicate that the proposed system can shorten incident response, strengthen accountability in crash investigations and recalls, and provide a practical foundation for privacy-preserving, transparent data collaboration between mobility operators and urban management departments.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69fc2b608b49bacb8b347817https://doi.org/10.1007/s44443-026-00813-4
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