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Rational multiparty computation.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Rational multiparty computation./
Author:	Wallrabenstein, John Ross.
Description:	1 online resource (171 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 76-12, Section: B.
Contained By:	Dissertations Abstracts International76-12B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9781321743951

Rational multiparty computation.
Wallrabenstein, John Ross.

Rational multiparty computation. - 1 online resource (171 pages)

Source: Dissertations Abstracts International, Volume: 76-12, Section: B.

Thesis (Ph.D.)--Purdue University, 2014.

Includes bibliographical references

The field of rational cryptography considers the design of cryptographic protocols in the presence of rational agents seeking to maximize local utility functions. This departs from the standard secure multiparty computation setting, where players are assumed to be either honest or malicious. We detail the construction of both a two-party and a multiparty game theoretic framework for constructing rational cryptographic protocols. Our framework specifies the utility function assumptions necessary to realize the privacy, correctness, and fairness guarantees for protocols. We demonstrate that our framework correctly models cryptographic protocols, such as rational secret sharing, where existing work considers equilibrium concepts that yield unreasonable equilibria. Similarly, we demonstrate that cryptography may be applied to the game theoretic domain, constructing an auction market not realizable in the original formulation. Additionally, we demonstrate that modeling players as rational agents allows us to design a protocol that destabilizes coalitions. Thus, we establish a mutual benefit from combining the two fields, while demonstrating the applicability of our framework to real-world market environments. We also give an application of game theory to adversarial interactions where cryptography is not necessary. Specifically, we consider adversarial machine learning, where the adversary is rational and reacts to the presence of a data miner. We give a general extension to classification algorithms that returns greater expected utility for the data miner than existing classification methods.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9781321743951Subjects--Topical Terms:

573171
Computer science.
Subjects--Index Terms:

CryptographyIndex Terms--Genre/Form:

554714
Electronic books.

Rational multiparty computation.
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500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Clifton, Christopher.
502 $a Thesis (Ph.D.)--Purdue University, 2014.
504 $a Includes bibliographical references
520 $a The field of rational cryptography considers the design of cryptographic protocols in the presence of rational agents seeking to maximize local utility functions. This departs from the standard secure multiparty computation setting, where players are assumed to be either honest or malicious. We detail the construction of both a two-party and a multiparty game theoretic framework for constructing rational cryptographic protocols. Our framework specifies the utility function assumptions necessary to realize the privacy, correctness, and fairness guarantees for protocols. We demonstrate that our framework correctly models cryptographic protocols, such as rational secret sharing, where existing work considers equilibrium concepts that yield unreasonable equilibria. Similarly, we demonstrate that cryptography may be applied to the game theoretic domain, constructing an auction market not realizable in the original formulation. Additionally, we demonstrate that modeling players as rational agents allows us to design a protocol that destabilizes coalitions. Thus, we establish a mutual benefit from combining the two fields, while demonstrating the applicability of our framework to real-world market environments. We also give an application of game theory to adversarial interactions where cryptography is not necessary. Specifically, we consider adversarial machine learning, where the adversary is rational and reacts to the presence of a data miner. We give a general extension to classification algorithms that returns greater expected utility for the data miner than existing classification methods.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
653 $a Cryptography
653 $a Game theory
653 $a Secure multiparty computation
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