@inproceedings{62f188ea78634f9ba705b39c3ca66315,
title = "An Approach for Distributing Sensitive Values in k-Anonymity",
abstract = "k-anonymity is a popular model in privacy preserving data publishing. It provides privacy guarantee when a microdata table is released. In microdata, sensitive attributes contain high-sensitive and low sensitive values. Unfortunately, study in anonymity for distributing sensitive value is still rare. This study aims to distribute evenly high-sensitive value to quasi identifier group. We proposed an approach called Simple Distribution of Sensitive Value. We compared our method with systematic clustering which is considered as very effective method to group quasi identifier. Information entropy is used to measure the diversity in each quasi identifier group and in a microdata table. Experiment result show our method outperformed systematic clustering when high-sensitive value is distributed.",
keywords = "high-sensitive value, k-anonymity, SDSV, simple distribution of sensitive values",
author = "Widodo and Budiardjo, {Eko K.} and Wibowo, {Wahyu C.} and Achsan, {Harry T.Y.}",
year = "2019",
month = oct,
doi = "10.1109/IWBIS.2019.8935849",
language = "English",
series = "2019 International Workshop on Big Data and Information Security, IWBIS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "109--114",
booktitle = "2019 International Workshop on Big Data and Information Security, IWBIS 2019",
address = "United States",
note = "2019 International Workshop on Big Data and Information Security, IWBIS 2019 ; Conference date: 11-10-2019",
}