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Improving Privacy With Intelligent Cooperative Caching In Vehicular Ad Hoc Networks
| Title: | Improving Privacy With Intelligent Cooperative Caching In Vehicular Ad Hoc Networks. |
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| Name(s): |
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 |
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| Type of Resource: | text | |
| Genre: | Electronic Thesis Or Dissertation | |
| Date Created: | 2017 | |
| Date Issued: | 2017 | |
| Publisher: | Florida Atlantic University | |
| Place of Publication: | Boca Raton, Fla. | |
| Physical Form: | application/pdf | |
| Extent: | 201 p. | |
| Language(s): | English | |
| Summary: | 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. | |
| Identifier: | FA00004965 (IID) | |
| Degree granted: | Dissertation (Ph.D.)--Florida Atlantic University, 2017. | |
| Collection: | FAU Electronic Theses and Dissertations Collection | |
| Note(s): | Includes bibliography. | |
| Subject(s): |
Dissertations, Academic -- Florida Atlantic University Public key infrastructure (Computer security) Privacy. Cache memory. Public key infrastructure (Computer security). |
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| Held by: | Florida Atlantic University Libraries | |
| Sublocation: | Digital Library | |
| Links: | http://purl.flvc.org/fau/fd/FA00004975 | |
| Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00004965 | |
| Use and Reproduction: | 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. | |
| Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
| Host Institution: | FAU | |
| Is Part of Series: | Florida Atlantic University Digital Library Collections. |
