Articles producció científica> Enginyeria Informàtica i Matemàtiques

Differentially private publication of database streams via hybrid video coding

  • Datos identificativos

    Identificador: imarina:9262256
    Autores:
    Parra-Arnau, JavierStrufe, ThorstenDomingo-Ferrer, Josep
    Resumen:
    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.
  • Otros:

    Autor según el artículo: Parra-Arnau, Javier; Strufe, Thorsten; Domingo-Ferrer, Josep
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Domingo Ferrer, Josep / PARRA ARNAU, JAVIER
    Palabras clave: Video encoding Privacy Database anonymization Data streams
    Resumen: 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.
    Áreas temáticas: 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
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: josep.domingo@urv.cat
    Identificador del autor: 0000-0001-7213-4962
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0950705122003665?via%3Dihub
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Knowledge-Based Systems. 247 108778-
    Referencia de l'ítem segons les normes 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
    DOI del artículo: 10.1016/j.knosys.2022.108778
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2022
    Tipo de publicación: Journal Publications
  • Palabras clave:

    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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