Welcome to the resource topic for 2016/781
Title:
Privately Matching k-mers
Authors: Justin Bed{ő}, Thomas Conway, Kim Ramchen, Vanessa Teague
Abstract:We construct the first noninteractive protocols for several tasks related to private set intersection. We provide efficient protocols for three related problems, each motivated by a particular kind of genomic testing. Set intersection with labelling hides the intersecting set itself and returns only the labels of the common elements, thus allowing a genomics company to return diagnoses without exposing the IP of its database. Fuzzy matching with labelling extends this to allow matching at a particular Hamming distance, which solves the same problem but incorporates the possibility of genetic variation. Closest matching returns the item in the server’s database closest to the client’s query - this can be used for taxonomic classification. Our protocols are optimised for the matching of k-mers (sets of k-length strings) rather than individual nucleotides, which is particularly useful for representing the short reads produced by next generation sequencing technologies.
ePrint: https://eprint.iacr.org/2016/781
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