Highly-Scalable Searchable Symmetric Encryption with Support for Boolean Queries

By David Cash, Stanislaw Jarecki, Charanjit S. Jutla, Hugo Krawczyk, Marcel-Catalin Rosu, Michael Steiner. IACR Cryptology ePrint Archive, 2013

961 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/effd352328e57bc7b68e0802b7c91be386b86614

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Raphael Bost
2. Jonathan Katz
3. Srinath T. V. Setty
4. Dan Boneh
5. Elaine Shi
6. Brent Waters
7. Xingming Sun
8. Xinhui Wang

In Computational Theory and Mathematics

1. Raphael Bost
2. Xingming Sun
3. Xinhui Wang
4. Zhihua Xia
5. Srinath T. V. Setty
6. Jonathan Katz
7. Michael Walfish
8. Elaine Shi

Citations in the corpus

• SHIELD: Scalable Homomorphic Implementation of Encrypted Data-Classifiers (2015, methodology): “E-mail: alhassan@ece.utoronto.ca • Glenn Gulak is with the Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada.”
• Forward and Backward Private Searchable Encryption from Constrained Cryptographic Primitives (2017, background): “Since the inception of searchable encryption, tremendous progress has been made toward efficient solutions yielding high throughput, low latency, and more expressive queries [CJJ + 13, CJJ + 14, MM17].”
• Scalable and Private Media Consumption with Popcorn (2016, background): “Similarly, searchable symmetric encryption (SSE) schemes (see [25, 26] for a survey of this area) are yet another solution for private data retrieval from a remote database.”
• Security and Privacy in the Internet of Things (2017, background): “During the past decade, many provably secure SSE schemes [56, 147, 48, 94, 93, 118, 47, 81, 135] have been proposed, which make trade-offs among security, search performance and storage overhead by exploring static- [56, 147, 48] and dynamic datasets [94, 93, 118, 47, 81, 135] as well as various dat”
• Dynamic Searchable Encryption via Blind Storage (2014, methodology): “Later, in Section V-B, we show how to build a Dynamic SSE scheme using a Blind Storage system.”
• Leakage-Abuse Attacks Against Searchable Encryption (2015, methodology): “, Figure 1 of [4]), such as the number of documents, number of unique keywords, and when the same query is repeated.”
• Practical Dynamic Searchable Encryption with Small Leakage (2014, methodology): “[5] who implemented a static, conjunctive searchable encryption scheme on enterprise-grade rotational hard-drives.”
• A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data (2016, methodology): “Due to the special structure of our tree-based index, the proposed search scheme can flexibly achieve sublinear search time and deal with the deletion and insertion of documents.”
• A Survey of Provably Secure Searchable Encryption (2014, neutral): “However, interactive protocols can achieve a higher level of security [Boneh et al. 2007; Bösch et al. 2012] or efficiency [Cash et al. 2013].”
• All Your Queries Are Belong to Us: The Power of File-Injection Attacks on Searchable Encryption (2016, background): “We consider both adaptive and non-adaptive attacks, where adaptivity refers (in part) to whether the server injects files before or after the client’s query is made.”
• Generic Attacks on Secure Outsourced Databases (2016, methodology): “Broadly, the techniques include multi-party computation [47, 24], oblivious RAM [25, 25], searchable symmetric and structural encryp-1330 tion [45, 22, 13, 15, 14, 12, 40, 19, 33], functional encryption [9, 43], property-preserving encryption [5, 1, 7, 39] and homomorphic encryption [10, 21].”
• ∑oφoς: Forward Secure Searchable Encryption (2016, methodology): “…first thing we can notice, is that, despite the use of costly asymmetric cryptographic primitives, we achieve higher search throughput with a single basic SSD than the authors of [CJJ + 13] (1E7 matches per second for Σ oφoς , versus 2E4 for large results queries), who use an expensive SAN system.”
• Dynamic Searchable Encryption in Very-Large Databases: Data Structures and Implementation (2014, methodology): “In experiments with configurations and data sets similar to those described in [3], the hash table has a load factor of ≈ 60% (i.e., over-sized by a factor of ≈ 1.6) for the placement to be successful, and goodput is ≈ 1%, as there are 96 locations per bucket.”