With the issuance of the Notice of Proposed Rule Making (NPRM) for Vehicle
to Vehicle (V2V) communications by the United States National Highway Tra c
Safety Administration (NHTSA), the goal of the widespread deployment of vehicular
networking has taken a signi cant step towards becoming a reality. In order for
consumers to accept the technology, it is expected that reasonable mechanisms will
be in place to protect their privacy. Cooperative Caching has been proposed as an
approach that can be used to improve privacy by distributing data items throughout
the mobile network as they are requested. With this approach, vehicles rst attempt
to retrieve data items from the mobile network, alleviating the need to send all requests
to a centralized location that may be vulnerable to an attack. However, with
this approach, a requesting vehicle may expose itself to many unknown vehicles as
part of the cache discovery process.
In this work we present a Public Key Infrastructure (PKI) based Cooperative
Caching system that utilizes a genetic algorithm to selectively choose members of the
mobile network to query for data items with a focus on improving overall privacy. The
privacy improvement is achieved by avoiding those members that present a greater risk of exposing information related to the request and choosing members that have a
greater potential of having the needed data item. An Agent Based Model is utilized
to baseline the privacy concerns when using a broadcast based approach to cache
discovery. In addition, an epidemiology inspired mathematical model is presented to
illustrate the impact of reducing the number of vehicles queried during cache discovery.
Periodic reports from neighboring vehicles are used by the genetic algorithm to
identify which neighbors should be queried during cache discovery. In order for the
system to be realistic, vehicles must trust the information in these reports. A PKI
based approach used to evaluate the trustworthiness of each vehicle in the system is
also detailed. We have conducted an in-depth performance study of our system that
demonstrates a signi cant reduction in the overall risk of exposure when compared
to broadcasting the request to all neighbors. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_39759 |
| Contributors | Glass, Stephen C. (author), Mahgoub, Imad (Thesis advisor), Florida Atlantic University (Degree grantor), College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Format | 201 p., application/pdf |
| Rights | Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
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