Blockchain-Based Access Control Framework for Autonomous Vehicle Data Sharing

Autonomous vehicles (AVs) generate vast amounts of data from onboard sensors, internal
systems, and their surrounding environments. Sharing this data, particularly in stored form,
is essential for enhancing safety, enabling post-event analysis, improving vehicle performance,
and supporting regulatory oversight. However, the sensitive nature of AV data introduces
significant challenges related to security, ownership, trust, and potential conflicts of interest
among multiple stakeholders. Addressing these challenges requires a robust and transparent
data-sharing framework that ensures traceability, accountability, and controlled access.
This research investigates blockchain technology as a foundation for secure and trustworthy
AV data sharing. Blockchain offers decentralisation, immutability, and fine-grained access
control, making it a strong candidate for managing sensitive automotive data. Among
available platforms, Hyperledger Fabric (HLF) is selected due to its permissioned architecture,
modular design, and support for customisable endorsement policies, which align with the
governance requirements of the automotive ecosystem.
The research presents the design, implementation, and evaluation of a multi-party
data-sharing framework for AVs using HLF and smart contracts. An additional contribution
is the reconfiguration of endorsement policies (EPs), which define the participants required to
validate transactions, to reflect real-world trust hierarchies. In particular, greater endorsement
authority is assigned to vehicle manufacturers, reflecting their central role in the data lifecycle.
To assess the implications of this design, three EP configurations are implemented and tested
under varying workloads, measuring throughput, latency, and transaction success rate.
The evaluation demonstrates that system throughput is constrained by architectural
bottlenecks, including peer processing capacity, single-orderer contention, and state database
overhead, rather than endorsement logic alone. User concurrency and chaincode complexity
are identified as key factors limiting scalability, with throughput reaching a stable ceiling
under increasing transaction loads. Among the evaluated configurations, Approach 2 shows
greater resilience under high workloads, while Approach 1 achieves lower latency under lighter
conditions. Furthermore, stricter endorsement policies improve security and accountability
but introduce measurable performance overheads, whereas relaxed policies enhance efficiency
at the cost of reduced resilience and potential centralisation.
These findings indicate that practical AV data-sharing systems need to consider the
alignment of endorsement policy design, chaincode complexity, and infrastructure provisioning
with expected workload characteristics. They also highlight that scalability limitations in
Hyperledger Fabric-based systems are driven primarily by system-level constraints rather
than policy configuration alone, emphasising the need for broader architectural optimisation.
Overall, this thesis presents a practical prototype for AV data sharing that integrates
blockchain’s capabilities with configurable governance mechanisms, offering valuable insights
for the design of data-sharing systems.