Protocols for Secure Remote Database Access with Approximate Matching

By Wenliang Du, Mikhail J. Atallah. 2001

162 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

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Citations in the corpus

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data (2017, methodology): “Our protocol can also be seen as a modification of the construction presented by Du and Attalah [20] where the trusted initializer does not keep a share of the result, and is presented in Figure 1.”
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications (2018, methodology): “(ii) The Du-Atallah protocol [36] is another method to perform multiplication on additive shared values which we describe next.”
Secure multi-party computation problems and their applications: a review and open problems (2001, background): “The authors of this paper have already studied some of these problems [12, 13, 14, 4].”
Secure Linear Regression on Vertically Partitioned Datasets (2016, methodology): “Our protocol is a modification of the construction presented by Du and Attalah [13] and is presented in Figure 3.”
A taxonomy of privacy-preserving record linkage techniques (2013, background): “Du01 : Du et al. [127] in 2001 suggested a secure approach for private remote database access with an untrusted third party that is assumed to not collude with any of the two database owners.”
Data Matching (2012, background): “[96] investigated this topic for different scenarios, including exact and approximate pattern matching.”
Random projection-based multiplicative data perturbation for privacy preserving distributed data mining (2006, background): “These problems include privacy preserving information retrieval [26], privacy preserving geometric computation [27], privacy preserving statistical analysis [28], [29], and privacy preserving scientific computations [30], etc.”