Toward a Secure and Decentralized Blockchain-Based Ride-Hailing Platform for Autonomous Vehicles
General Material Designation
[Thesis]
First Statement of Responsibility
Shivers, Ryan M.
Subsequent Statement of Responsibility
Ghafoor, Sheikh K.
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
Tennessee Technological University
Date of Publication, Distribution, etc.
2019
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
95
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
M.S.
Body granting the degree
Tennessee Technological University
Text preceding or following the note
2019
SUMMARY OR ABSTRACT
Text of Note
Ride-hailing and ride-sharing applications have recently gained in popularity as a convenient alternative to traditional modes of travel. Current research into autonomous vehicles is accelerating rapidly and will soon become a critical component of a ride-hailing platform's architecture. Implementing an autonomous vehicle ride-hailing platform proves a difficult challenge due to the centralized nature of traditional ride-hailing architectures. In a traditional ride-hailing environment the drivers operate their own personal vehicles so it follows that a fleet of autonomous vehicles would be required for a centralized ride-hailing platform to succeed. Decentralization of the ride-hailing platform would remove a road block along the way to an autonomous vehicle ride-hailing platform by allowing owners of autonomous vehicles to add their vehicle to a community driven fleet when not in use. Blockchain technology is an attractive choice for this decentralized architecture due to its immutability and fault tolerance. This thesis proposes a framework for developing a decentralized ride-hailing architecture that is verifiably secure. Implementation of this framework uses Hyperledger Fabric and evaluation of the implementation is done by applying known security models, utilizing a chaincode static analysis tool, and performing a performance analysis under heavy network load.