IEEE Transactions on Knowledge and Data Engineering · 2014 · 66 citations · 33 references
ComputingComputer ScienceCryptographyData StructuresPrivacy EngineeringData AnonymizationData De-identificationData ProtectionDifferential PrivacyHash FunctionsPrivacy-preserving ProtocolsAnonymizationAnonymization AlgorithmsBlockingDe-anonymizationHashingLocality-sensitive HashingMicrodata AnonymizationPrivacy-preserving Data Linkage
We present a Λ-fold Redundant Blocking Framework, that relies on the Locality-Sensitive Hashing technique for identifying candidate record pairs, which have undergone an anonymization transformation. In this context, we demonstrate the usage and evaluate the performance of a variety of families of hash functions used for blocking. We illustrate that the performance attained is highly correlated to the distance-preserving properties of the anonymization format used. The parameters, of the blocking scheme, are optimally selected so that we achieve the highest possible accuracy in the least possible running time. We also introduce an SMC-based protocol in order to compare the formulated record pairs homomorphically, without running the risk of breaching the privacy of the underlying records.
33
Similarity Search in High Dimensions via Hashing
Aristides Gionis, Piotr Indyk, Rajeev Motwani · 1999 · 3.1K citations
Locality-sensitive hashing scheme based on p-stable distributions
Mayur Datar, Nicole Immorlica, Piotr Indyk et al. · 2004 · 3K citations