Secure and practical computation on encrypted data

Naveed, Muhammad

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https://hdl.handle.net/2142/90606 Copy

Description

Title

Secure and practical computation on encrypted data

Author(s)

Naveed, Muhammad

Issue Date

2016-04-21

Director of Research (if dissertation) or Advisor (if thesis)

• Gunter, Carl A.
• Prabhakaran, Manoj

Doctoral Committee Chair(s)

• Gunter, Carl A.
• Prabhakaran, Manoj

Committee Member(s)

• Borisov, Nikita
• Shi, Elaine
• Wang, XiaoFeng

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• computation on encrypted data
• property-preserving encryption
• symmetric searchable encryption
• controlled functional encryption

Abstract

Because of the importance of computing on data with privacy protections, the cryptographic community has developed both theoretical and practical solutions to compute on encrypted data. On the one hand, theoretical schemes, such as fully homomorphic encryption and functional encryption, are secure but extremely inefficient. On the other hand, practical schemes, such as property-preserving encryption, gain efficiency by accepting significant reductions in security. In this thesis, we first study the security of popular property-preserving encryption schemes that are being used by companies such as Microsoft and Google. We show that such schemes are unacceptably insecure for key target applications such as electronic medical records. Second, we propose new models to compute on encrypted data and develop efficient constructions and systems. We propose a new cryptographic primitive called Blind Storage and show how it can be used to realize symmetric searchable encryption, which is much more secure than property-preserving encryption. Finally, we propose a new cryptographic model called Controlled Functional Encryption and develop two efficient schemes in this model.

Graduation Semester

2016-05

Type of Resource

text

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http://hdl.handle.net/2142/90606

Copyright and License Information

Copyright 2016 Muhammad Naveed

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