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TITLE:
Improving multivariate microaggregation through hamiltonian paths and optimal univariate microaggregation - imarina:9217400

URV's Author/s:Alkhoury, Nadine / Casino Cembellín, Francisco José / Solanas Gómez, Agustín
Author, as appears in the article.:Maya-Lopez, Armando; Casino, Fran; Solanas, Agusti
Author's mail:franciscojose.casino@urv.cat
nadine.alkhoury@estudiants.urv.cat
nadine.alkhoury@estudiants.urv.cat
nadine.alkhoury@estudiants.urv.cat
nadine.alkhoury@estudiants.urv.cat
agusti.solanas@urv.cat
Author identifier:0000-0003-4296-2876
0000-0002-4881-6215
Journal publication year:2021
Publication Type:Journal Publications
APA:Maya-Lopez, Armando; Casino, Fran; Solanas, Agusti (2021). Improving multivariate microaggregation through hamiltonian paths and optimal univariate microaggregation. Symmetry-Basel, 13(6), 916-. DOI: 10.3390/sym13060916
Papper original source:Symmetry-Basel. 13 (6): 916-
Abstract:The collection of personal data is exponentially growing and, as a result, individual privacy is endangered accordingly. With the aim to lessen privacy risks whilst maintaining high degrees of data utility, a variety of techniques have been proposed, being microaggregation a very popular one. Microaggregation is a family of perturbation methods, in which its principle is to aggregate personal data records (i.e., microdata) in groups so as to preserve privacy through k-anonymity. The multivariate microaggregation problem is known to be NP-Hard; however, its univariate version could be optimally solved in polynomial time using the Hansen-Mukherjee (HM) algorithm. In this article, we propose a heuristic solution to the multivariate microaggregation problem inspired by the Traveling Salesman Problem (TSP) and the optimal univariate microaggregation solution. Given a multivariate dataset, first, we apply a TSP-tour construction heuristic to generate a Hamiltonian path through all dataset records. Next, we use the order provided by this Hamiltonian path (i.e., a given permutation of the records) as input to the Hansen-Mukherjee algorithm, virtually transforming it into a multivariate microaggregation solver we call Multivariate Hansen-Mukherjee (MHM). Our intuition is that good solutions to the TSP would yield Hamiltonian paths allowing the Hansen-Mukherjee algorithm to find good solutions to the multivariate microaggregation problem. We have tested our method with well-known benchmark datasets. Moreover, with the aim to show the usefulness of our approach to protecting location privacy, we have tested our solution with real-life trajectories datasets, too. We have compared the results of our algorithm with those of the best performing solutions, and we show that our proposal reduces the information loss resulting from the microaggregation. Overall, results suggest that transforming the multivariate microaggregation problem into its univariate counterpart by ordering microdata records with a proper Hamiltonian path and applying an optimal univariate solution leads to a reduction of the perturbation error whilst keeping the same privacy guarantees.
Article's DOI:10.3390/sym13060916
Link to the original source:https://www.mdpi.com/2073-8994/13/6/916
Papper version:info:eu-repo/semantics/publishedVersion
licence for use:https://creativecommons.org/licenses/by/3.0/es/
Department:Enginyeria Informàtica i Matemàtiques
Licence document URL:https://repositori.urv.cat/ca/proteccio-de-dades/
Thematic Areas:Visual arts and performing arts
Physics and astronomy (miscellaneous)
Multidisciplinary sciences
Modeling and simulation
Mathematics, interdisciplinary applications
Mathematics (miscellaneous)
Mathematics (all)
Matemática / probabilidade e estatística
General mathematics
Engineering (miscellaneous)
Computer science (miscellaneous)
Ciência da computação
Chemistry (miscellaneous)
Arts and humanities (miscellaneous)
Architecture
Applied mathematics
Keywords:Traveling salesman problem
Statistical disclosure control
Microaggregation
Location privacy
Graph theory
Data privacy
traveling salesman problem
statistical disclosure control
privacy
location privacy
graph theory
data-oriented microaggregation
data privacy
algorithm
Entity:Universitat Rovira i Virgili
Record's date:2024-10-12
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