Articles producció científica> Enginyeria Informàtica i Matemàtiques

Some basics on privacy techniques, anonymization and their big data challenges

  • Identification data

    Identifier: imarina:5132532
    Authors:
    Salas J, Domingo-Ferrer J
    Abstract:
    © 2018, Springer International Publishing AG, part of Springer Nature. With the progress in the information and communication fields, new opportunities and technologies for statistical analysis, knowledge discovery, data mining, and many other research areas have emerged, together with new challenges for privacy and data protection. Nowadays several personal records are kept in computerized databases. Personal data is collected and kept in census databases, medical databases, employee databases, among others. There has always been an asymmetry between the benefits of computerized databases and the rights of individual data subjects. Some data protection principles can be derived from the legal framework. In this survey, we present some basic cryptographic and non-cryptographic techniques that may be used for enhancing privacy, we focus mainly on anonymization in databases and networks, discuss some differences and interactions among the well-known models of k-anonymity and differential privacy and finally present some challenges to privacy that come from big data analytics.
  • Others:

    Author, as appears in the article.: Salas J, Domingo-Ferrer J
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Domingo Ferrer, Josep
    Keywords: Privacy enhancing technologies Privacy by design statistical disclosure Differential privacy Control k-anonymity Big data privacy
    Abstract: © 2018, Springer International Publishing AG, part of Springer Nature. With the progress in the information and communication fields, new opportunities and technologies for statistical analysis, knowledge discovery, data mining, and many other research areas have emerged, together with new challenges for privacy and data protection. Nowadays several personal records are kept in computerized databases. Personal data is collected and kept in census databases, medical databases, employee databases, among others. There has always been an asymmetry between the benefits of computerized databases and the rights of individual data subjects. Some data protection principles can be derived from the legal framework. In this survey, we present some basic cryptographic and non-cryptographic techniques that may be used for enhancing privacy, we focus mainly on anonymization in databases and networks, discuss some differences and interactions among the well-known models of k-anonymity and differential privacy and finally present some challenges to privacy that come from big data analytics.
    Thematic Areas: Mathematics, applied Computational theory and mathematics Computational mathematics Applied mathematics
    ISSN: 16618289
    Author's mail: josep.domingo@urv.cat
    Author identifier: 0000-0001-7213-4962
    Last page: 274
    Record's date: 2023-02-18
    Journal volume: 12
    Papper version: info:eu-repo/semantics/submittedVersion
    Link to the original source: https://link.springer.com/article/10.1007/s11786-018-0344-6
    Papper original source: Mathematics In Computer Science. 12 (3): 263-274
    APA: Salas J, Domingo-Ferrer J (2018). Some basics on privacy techniques, anonymization and their big data challenges. Mathematics In Computer Science, 12(3), 263-274. DOI: 10.1007/s11786-018-0344-6
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1007/s11786-018-0344-6
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2018
    First page: 263
    Publication Type: Journal Publications
  • Keywords:

    Applied Mathematics,Computational Mathematics,Computational Theory and Mathematics,Mathematics, Applied
    Privacy enhancing technologies
    Privacy by design statistical disclosure
    Differential privacy
    Control k-anonymity
    Big data privacy
    Mathematics, applied
    Computational theory and mathematics
    Computational mathematics
    Applied mathematics
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