國立虎尾科技大學 |

Protecting Data Privacy in the Presence of Data Provenance.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Protecting Data Privacy in the Presence of Data Provenance./
Author:	Kianmajd, Parisa.
Description:	1 online resource (174 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9780355151480

Protecting Data Privacy in the Presence of Data Provenance.
Kianmajd, Parisa.

Protecting Data Privacy in the Presence of Data Provenance. - 1 online resource (174 pages)

Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.

Thesis (Ph.D.)--University of California, Davis, 2017.

Includes bibliographical references

Provenance describes the origin, derivation, and ownership of data products. It enhances the trustworthiness and facilitates access and usage control decisions in information flow systems and distributed settings. Provenance may contain private information, be subject to multiple access policies or be too detailed, thus, the provenance may need to be sanitized before release.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355151480Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Protecting Data Privacy in the Presence of Data Provenance.
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245 1 0 $a Protecting Data Privacy in the Presence of Data Provenance.
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300 $a 1 online resource (174 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
500 $a Adviser: Karl Levitt.
502 $a Thesis (Ph.D.)--University of California, Davis, 2017.
504 $a Includes bibliographical references
520 $a Provenance describes the origin, derivation, and ownership of data products. It enhances the trustworthiness and facilitates access and usage control decisions in information flow systems and distributed settings. Provenance may contain private information, be subject to multiple access policies or be too detailed, thus, the provenance may need to be sanitized before release.
520 $a The main goal of this dissertation is to improve provenance sanitization methods by managing the conflicts between provenance and privacy policies and to present cryptographic solutions to protect the privacy of data and its provenance.
520 $a We use a model-based diagnosis approach to identify the conflicts in a set of policies and show how our framework can be used to find the conflicts between disclosure and privacy policies when sanitizing workflow provenance graphs.
520 $a Lack of trust is a prevalent issue in many applications. Blockchain technology makes the trust more transparent by making transactions' provenance public but this comes at the cost of compromising users' privacy. We present a cryptographic layer that can be applied over blockchain to mitigate privacy implications and allow users own and control their data.
520 $a We propose a privacy-preserving road usage charge system in which a network of peer drivers work together to record their location points periodically. The users can then answer various queries over their location points and compute cryptographic proofs showing that the query answers are accurate, and present the proofs together with the answers to the requesters. Also, we present a blockchain-based system for coordinating actions in smart communities in a privacy-preserving manner and look at its application for sharing solar energy in a smart neighborhood autonomously and without any third party being involved.
520 $a We also explore cryptographic approaches for providing an access control layer in emerging applications of blockchain technology. Despite numerous cryptographic access control approaches for the cloud systems, most of them are computationally too complex to be applied to practical cases. We describe how blockchain can change this paradigm by deploying the power of a peer-to-peer network for granting and verifying access requests.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Davis. $b Computer Science. $3 1182372
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10285159 $z click for full text (PQDT)