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- W2954358533 abstract "In the information age, people’s various behavioral data are collected in large quantities. The sharing of information makes it convenient for some scientific investigations, but there is a leakage of personal privacy at the same time. The current research on privacy preservation is mostly based on relational tables or social network graphs. This paper focuses on semi-structured data, which is often ignored in privacy preservation. We propose a new privacy guarantee called X-km-anonymity and propose a bottom-up heuristic algorithm that provides protection by satisfying X-km-anonymity. We verified the feasibility of the algorithm through a reliable utility analysis method on the simulation data." @default.
- W2954358533 created "2019-07-12" @default.
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- W2954358533 date "2019-06-14" @default.
- W2954358533 modified "2023-09-25" @default.
- W2954358533 title "Privacy Preservation of Semi-structured Data Based on XML" @default.
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- W2954358533 doi "https://doi.org/10.1007/978-981-13-6508-9_131" @default.
- W2954358533 hasPublicationYear "2019" @default.
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