Articles producció científica> Enginyeria Informàtica i Matemàtiques

Differentially private publication of database streams via hybrid video coding

  • Identification data

    Identifier: imarina:9262256
    Authors:
    Parra-Arnau, JavierStrufe, ThorstenDomingo-Ferrer, Josep
    Abstract:
    While most anonymization technology available today is designed for static and small data, the current picture is of massive volumes of dynamic data arriving at unprecedented velocities. From the standpoint of anonymization, the most challenging type of dynamic data is data streams. However, while the majority of proposals deal with publishing either count-based or aggregated statistics about the underlying stream, little attention has been paid to the problem of continuously publishing the stream itself with differential privacy guarantees. In this work, we propose an anonymization method that can publish multiple numerical-attribute, finite microdata streams with high protection as well as high utility, the latter aspect measured as data distortion, delay and record reordering. Our method, which relies on the well-known differential pulse-code modulation scheme, adapts techniques originally intended for hybrid video encoding, to favor and leverage dependencies among the blocks of the original stream and thereby reduce data distortion. The proposed solution is assessed experimentally on two of the largest data sets in the scientific community working in data anonymization. Our extensive empirical evaluation shows the trade-off among privacy protection, data distortion, delay and record reordering, and demonstrates the suitability of adapting video-compression techniques to anonymize database streams.
  • Others:

    Author, as appears in the article.: Parra-Arnau, Javier; Strufe, Thorsten; Domingo-Ferrer, Josep
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Domingo Ferrer, Josep / PARRA ARNAU, JAVIER
    Keywords: Video encoding Privacy Database anonymization Data streams
    Abstract: While most anonymization technology available today is designed for static and small data, the current picture is of massive volumes of dynamic data arriving at unprecedented velocities. From the standpoint of anonymization, the most challenging type of dynamic data is data streams. However, while the majority of proposals deal with publishing either count-based or aggregated statistics about the underlying stream, little attention has been paid to the problem of continuously publishing the stream itself with differential privacy guarantees. In this work, we propose an anonymization method that can publish multiple numerical-attribute, finite microdata streams with high protection as well as high utility, the latter aspect measured as data distortion, delay and record reordering. Our method, which relies on the well-known differential pulse-code modulation scheme, adapts techniques originally intended for hybrid video encoding, to favor and leverage dependencies among the blocks of the original stream and thereby reduce data distortion. The proposed solution is assessed experimentally on two of the largest data sets in the scientific community working in data anonymization. Our extensive empirical evaluation shows the trade-off among privacy protection, data distortion, delay and record reordering, and demonstrates the suitability of adapting video-compression techniques to anonymize database streams.
    Thematic Areas: Software Matemática / probabilidade e estatística Management information systems Interdisciplinar Information systems and management Información y documentación Engenharias iv Engenharias iii Economia Computer science, artificial intelligence Ciencias sociales Ciências biológicas i Ciência da computação Astronomia / física Artificial intelligence Administração pública e de empresas, ciências contábeis e turismo
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: josep.domingo@urv.cat
    Author identifier: 0000-0001-7213-4962
    Record's date: 2024-10-12
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/pii/S0950705122003665?via%3Dihub
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Knowledge-Based Systems. 247 108778-
    APA: Parra-Arnau, Javier; Strufe, Thorsten; Domingo-Ferrer, Josep (2022). Differentially private publication of database streams via hybrid video coding. Knowledge-Based Systems, 247(), 108778-. DOI: 10.1016/j.knosys.2022.108778
    Article's DOI: 10.1016/j.knosys.2022.108778
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    Artificial Intelligence,Computer Science, Artificial Intelligence,Information Systems and Management,Management Information Systems,Software
    Video encoding
    Privacy
    Database anonymization
    Data streams
    Software
    Matemática / probabilidade e estatística
    Management information systems
    Interdisciplinar
    Information systems and management
    Información y documentación
    Engenharias iv
    Engenharias iii
    Economia
    Computer science, artificial intelligence
    Ciencias sociales
    Ciências biológicas i
    Ciência da computação
    Astronomia / física
    Artificial intelligence
    Administração pública e de empresas, ciências contábeis e turismo
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