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Effcient Implementation and Computational Analysis of Privacy-Preserving Protocols for Securing the Financial Markets
| Title: | Effcient Implementation and Computational Analysis of Privacy-Preserving Protocols for Securing the Financial Markets. |
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| Name(s): |
Alvarez, Ramiro, author Nojoumian, Mehrdad, 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: | 2018 | |
| Date Issued: | 2018 | |
| Publisher: | Florida Atlantic University | |
| Place of Publication: | Boca Raton, Fla. | |
| Physical Form: | application/pdf | |
| Extent: | 68 p. | |
| Language(s): | English | |
| Abstract/Description: | Auctions are a key economic mechanism for establishing the value of goods that have an uncertain price. In recent years, as a consequence of the ubiquitous emergence of technology, auctions can reach consumers, and as a result drive market prices, on a global scale. Collection of private information such as past trades exposes more information than desired by market participants. The leaked information can be statistically analyzed to provide auctioneers, or competitors, an advantage on future transactions. The need to preserve privacy has become a critical concern to reach an accepted level of fairness, and to provide market participants an environment in which they can bid a true valuation. This research is about possible mechanisms to carry out sealed-bid auctions in a distributed setting, and provides the reader with the challenges that currently persevere in the field. The first chapter offers an introduction to different kinds of auction, and to describe sealed-bid auction. The next chapter surveys the literature, and provides necessary theoretical background. Moving on to chapter 3, instead of solely focusing on theoretical aspects of sealed-bid auctions, this chapter dives into implementation details, and demonstrates through communication and computational analysis how different settings affect performance. | |
| Identifier: | FA00013051 (IID) | |
| Degree granted: | Thesis (M.S.)--Florida Atlantic University, 2018. | |
| Collection: | FAU Electronic Theses and Dissertations Collection | |
| Note(s): | Includes bibliography. | |
| Subject(s): |
Auctions. Financial markets. Tender offers (Securities). |
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| Held by: | Florida Atlantic University Libraries | |
| Sublocation: | Digital Library | |
| Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00013051 | |
| 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. |
