Doctoral Dissertations

Keywords and Phrases

Cloud; Encryption; Query processing

Abstract

"The query processing of relational data has been studied extensively throughout the past decade. A number of theoretical and practical solutions to query processing have been proposed under various scenarios. With the recent popularity of cloud computing, data owners now have the opportunity to outsource not only their data but also data processing functionalities to the cloud. Because of data security and personal privacy concerns, sensitive data (e.g., medical records) should be encrypted before being outsourced to a cloud, and the cloud should perform query processing tasks on the encrypted data only. These tasks are termed as Privacy-Preserving Query Processing (PPQP) over encrypted data. Based on the concept of Secure Multiparty Computation (SMC), SMC-based distributed protocols were developed to allow the cloud to perform queries directly over encrypted data. These protocols protect the confidentiality of the stored data, user queries, and data access patterns from cloud service providers and other unauthorized users. Several queries were considered in an attempt to create a well-defined scope. These queries included the k-Nearest Neighbor (kNN) query, advanced analytical query, and correlated range query. The proposed protocols utilize an additive homomorphic cryptosystem and/or a garbled circuit technique at different stages of query processing to achieve the best performance. In addition, by adopting a multi-cloud computing paradigm, all computations can be done on the encrypted data without using very expensive fully homomorphic encryptions. The proposed protocols' security was analyzed theoretically, and its practicality was evaluated through extensive empirical results"--Abstract, page iii.

Advisor(s)

Jiang, Wei

Committee Member(s)

Hurson, A. R.
Lin, Dan
Wen, Xuerong
Yin, Zhaozheng

Department(s)

Computer Science

Degree Name

Ph. D. in Computer Science

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2015

Pagination

ix, 108 pages

Note about bibliography

Includes bibliographic references (pages 101-107).

Rights

© 2015 Yousef M. Elmehdwi, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Cloud computing -- Security measures
Querying (Computer science)
Data encryption (Computer science)
Data protection

Thesis Number

T 10819

Electronic OCLC #

936206885

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