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2010•Computer Engineering and Applications JournalRequires access

Enhanced privacy preserving K-anonymity model:(α,L)-diversity K-anonymity

Tianjie Cao

Open publisher page 3 citations

Abstract

K-anonymity is a popular model used in microdata publishing to protect individual privacy.This paper finds that there are privacy disclosure problems on the current K-anonymity models.A new K-anonymity model called(α,L)-diversity K-anonymity is proposed to solve the existing problems.It is also validated by a local-recoding generalization algorithm.

About this research paper

What this paper is about

K-anonymity is a popular model used in microdata publishing to protect individual privacy.This paper finds that there are privacy disclosure problems on the current K-anonymity models.A new K-anonymity model called(α,L)-diversity K-anonymity is proposed to solve the existing problems.It is also validated by a local-recoding generalization algorithm.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

K-anonymity is a popular model used in microdata publishing to protect individual privacy.This paper finds that there are privacy disclosure problems on the current K-anonymity models.A new K-anonymity model called(α,L)-diversity K-anonymity is proposed to solve the existing problems.It is also validated by a local-recoding generalization algorithm.

Key concepts: Anonymity, Microdata (statistics), k-anonymity, Computer science, Data publishing, Generalization, Internet privacy, Computer security

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