Title
Masking Fuzzy-Searchable Public Databases.
Abstract
We introduce and study the notion of keyless fuzzy search (KlFS) which allows to mask a publicly available database in such a way that any third party can retrieve content if and only if it possesses some data that is "close to" the encrypted data - no cryptographic keys are involved. We devise a formal security model that asks a scheme not to leak any information about the data and the queries except for some well-defined leakage function if attackers cannot guess the right query to make. In particular, our definition implies that recovering high entropy data protected with a KlFS scheme is costly. We propose two KlFS schemes: both use locality-sensitive hashes (LSH), cryptographic hashes and symmetric encryption as building blocks. The first scheme, is generic and works for abstract plaintext domains. The second scheme is specifically suited for databases of images. To demonstrate the feasibility of our KlFS for images, we implemented and evaluated a prototype system that supports image search by object similarity on masked database.
Year
DOI
Venue
2019
10.1007/978-3-030-21568-2_28
Lecture Notes in Computer Science
Keywords
Field
DocType
Keyless searchable encryption,LSH,Image search
Symmetric-key algorithm,Computer science,Cryptography,Theoretical computer science,Encryption,Hash function,Approximate string matching,Key (cryptography),Database,Plaintext,Computer security model
Journal
Volume
ISSN
Citations 
11464
0302-9743
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Alexandra Boldyreva12297114.80
Tianxin Tang200.34
Bogdan Warinschi3151468.98