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Title: Searchable Encryption Revisited
Tianxin Tang
Ph.D. Student in Computer Science
School of Computer Science
College of Computing
Georgia Institute of Technology
Date: Wed December 9 2020
Time: 10:00 AM to 11:30 AM (EST)
Location: (remote via Bluejeans) https://bluejeans.com/801214521
Committee
- Dr. Sasha Boldyreva (Advisor, School of Computer Science, Georgia Institute of Technology, US)
- Dr. Vlad Kolesnikov (School of Computer Science, Georgia Institute of Technology, US)
- Dr. Wenke Lee (School of Computer Science, Georgia Institute of Technology, US)
- Dr. Bogdan Warinschi (Department of Computer Science, University of Bristol, UK)
Abstract
The past decade has witnessed increasing demands from corporations and
individuals on data outsourcing to third-party cloud providers. How can the
service provider offer search functionality without sacrificing clients' data
privacy remains an intriguing problem. Searchable encryption (SE), is an area
that explicitly targets the outsourced setting, offering privacy-preserving
solutions for accessing the encrypted data. We revisit SE and focus on more
versatile functionalities: first, similarity search in a keyless setting;
second, secure approximate k-NN search. Due to emerging leakage-abusing attacks
in SE, we also consider the third problem, constructing a practical SE
supporting keyword search with minimal leakage.
We adopt a provable security approach attacking the above problems: define the
syntax, correctness, security sufficient for practice; propose constructions
meeting the correctness and security requirements, only relying on standard
cryptographic hardness assumptions. For the first problem, how to conduct
similarity search without the secret keys, we propose a non-interactive protocol
called keyless fuzzy search (KlFS). It masks public fuzzy-searchable databases
so that only users who possess close data to parts of the database can access
the masked contents. The security level of the construction relies on the
"closeness-unpredictability” property of the database. For the second problem,
secure approximate k-NN search, we show how to utilize ORAM techniques and
construct a privacy-preserving approximate k-NN protocol that hides the access
pattern, query pattern, and volume pattern. Finally, for the last problem, we
focus on a strong security notion of searchable encryption with keyword search
that hides access, query, and volume pattern. We propose a practical ORAM-based
construction, more efficient than known ORAM-based ones, and more secure than
available structured encryption schemes.
