4.4 Article

Efficient Searchable Encryption Through Compression

Journal

PROCEEDINGS OF THE VLDB ENDOWMENT
Volume 11, Issue 11, Pages 1729-1741

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.14778/3236187.3236218

Keywords

-

Funding

  1. NSF [1514261, 1526950, 1652259]
  2. National Institute of Standards and Technology
  3. Google faculty research award
  4. Yahoo! faculty research engagement program
  5. NetApp faculty fellowship
  6. Symantec PhD fellowship
  7. Division Of Computer and Network Systems
  8. Direct For Computer & Info Scie & Enginr [1652259] Funding Source: National Science Foundation
  9. Division Of Computer and Network Systems
  10. Direct For Computer & Info Scie & Enginr [1514261, 1526950] Funding Source: National Science Foundation

Ask authors/readers for more resources

In this work we design new searchable encryption schemes whose goal is to minimize the number of cryptographic operations required to retrieve the result a dimension mostly overlooked by previous works, yet very important in practice. Our main idea is to utilize compression so as to reduce the size of the plaintext indexes before producing the encrypted searchable indices. Our solution can use any existing Searchable Encryption (SE) scheme as a black-box and any combination of lossless compression algorithms, without compromising security. The efficiency of our schemes varies based on the leakage exposed by the underlying application. For instance, for private keyword search (more leakage), we demonstrate up to 188x savings in search time, while for database search (less leakage) our savings are up to 62x. The power of our approach is better manifested when combined with more secure, yet less practical, cryptographic tools, such as Oblivious Random Access Memory (ORAM). In particular while ORAM is known to be prohibitively expensive for large-scale applications, we show that our compress-first-ORAM-next approach allows significant more efficient index search time, reducing the time for executing a query with result of size more than one million tuples from approximately 21 hours to 20 minutes.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available