A Privacy-Preserving Index for Range Queries

By Bijit Hore, Sharad Mehrotra, Gene Tsudik. Very Large Data Bases Conference, 2004

510 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/1b1f5895f3861155777332f1959b3cbee4449332

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

In Management Science and Operations Research

Citations in the corpus

Deterministic and Efficiently Searchable Encryption (2007, background): “Sub-linear time searchable encryption has been much targeted by the database security community [45, 3, 36, 25, 38, 39, 41, 37, 19, 51].”
Privacy-Preserving Queries over Relational Databases (2010, background): “The restriction is crucial in situations where the database privacy is equally of concern.”
Generic Attacks on Secure Outsourced Databases (2016, background): “…can be divided into three categories; (i) bucketization techniques that partition the domain space and group data records before indexing (e.g. [27, 29, 28]), (ii) order-preserving encryption schemes that use deterministic encryption which ensures that the order of the cypher-texts is the same as…”
TrustedDB: A Trusted Hardware-Based Database with Privacy and Data Confidentiality (2011, background): “In [21], the authors explore optimal bucket sizes for range queries.”
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms (2008, methodology): “One representative work in the recent years is the privacy-preserving indexing technique proposed by Hore, Mehrotra and Tsudik for supporting efficient query evaluation over encrypted data [33].”
A General Survey of Privacy-Preserving Data Mining Models and Algorithms (2008, methodology): “This tradeoff has been studied in [55], and it has been shown that reasonable query precision can be maintained at the expense of partial disclosure.”
Privacy preserving decision tree learning over multiple parties (2007, background): “In addition to these, there are several proposals in privacy preserving data outsourcing [20] [21], which propose a new approach for data management, i.e., database as a service, and the goal is to protect the content of the data from database service provider while ensuring efficient query…”
Dynamic authenticated index structures for outsourced databases (2006, background): “In particular, query execution assurance of [30] does not provide authentication: the server could pass the challenges and yet still return false query results.”
Querying imprecise data in moving object environments (2003, background): “Recently, Hore et al. [ 11 ] discussed a privacypreserving index for querying range queries over encrypted data.”
Secure k-nearest neighbor query over encrypted data in outsourced environments (2013, methodology): “In the literature, various techniques related to query processing over encrypted data have been proposed, including range queries [6]–[8] and other aggregate queries [9], [10].”