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Jayapradha et al., 2022 - Google Patents

f-Slip: an efficient privacy-preserving data publishing framework for 1: M microdata with multiple sensitive attributes

Jayapradha et al., 2022

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Document ID
15907054982696904871
Author
Jayapradha J
Prakash M
Publication year
Publication venue
Soft Computing

External Links

Snippet

Privacy-preserving data publishing is a process of releasing the anonymized dataset for various purposes of analysis and research. Earlier, researchers have dealt with datasets considering it would contain only one record for an individual [1: 1 dataset], which is …
Continue reading at www.researchsquare.com (PDF) (other versions)

Classifications

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    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • G06F21/6254—Protecting personal data, e.g. for financial or medical purposes by anonymising data, e.g. decorrelating personal data from the owner's identification
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    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
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    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01—Social networking

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