Publication detail

Privacy-preserving Data Splitting: A Combinatorial Approach

Farras O. Ribes-Gonzales J. Ricci S.

Original Title

Privacy-preserving Data Splitting: A Combinatorial Approach

Type

journal article in Web of Science

Language

English

Original Abstract

Privacy-preserving data splitting is a technique that aims to protect data privacy by storing different fragments of data in different locations. In this work we give a new combinatorial formulation to the data splitting problem. We see the data splitting problem as a purely combinatorial problem, in which we have to split data attributes into different fragments in a way that satisfies certain combinatorial properties derived from processing and privacy constraints. Using this formulation, we develop new combinatorial and algebraic techniques to obtain solutions to the data splitting problem. We present an algebraic method which builds an optimal data splitting solution by using Grobner bases. Since this method is not efficient in general, we also develop a greedy algorithm for finding solutions that are not necessarily minimally sized.

Keywords

Data splitting; Data privacy; Graph colorings

Authors

Farras O.; Ribes-Gonzales J.; Ricci S.

Released

22. 5. 2021

Publisher

Springer

ISBN

0925-1022

Periodical

DESIGNS CODES AND CRYPTOGRAPHY

Year of study

89

Number

7

State

United States of America

Pages from

1735

Pages to

1756

Pages count

22

URL

http://link.springer.com/article/10.1007/s10623-021-00884-6

BibTex

@article{BUT171635,
  author="Sara {Ricci} and Oriol {Farras} and Jordi {Ribes-Gonzales}",
  title="Privacy-preserving Data Splitting: A Combinatorial Approach",
  journal="DESIGNS CODES AND CRYPTOGRAPHY",
  year="2021",
  volume="89",
  number="7",
  pages="1735--1756",
  doi="10.1007/s10623-021-00884-6",
  issn="0925-1022",
  url="http://link.springer.com/article/10.1007/s10623-021-00884-6"
}