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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/16235
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| タイトル: | Anonymization Technique based on SGD Matrix Factrization |
| 著者: | Mimoto, Tomoaki
Hidano, Seira
Kiyomoto, Shinsaku
Miyaji, Atsuko |
| キーワード: | time-sequence data
anonymization
matrix factorization
privacy and utility |
| 発行日: | 2020-02-01 |
| 出版者: | 電子情報通信学会 |
| 誌名: | IEICE Transactions on Information and Systems |
| 巻: | E103-D |
| 号: | 2 |
| 開始ページ: | 299 |
| 終了ページ: | 308 |
| DOI: | 10.1587/transinf.2019INP0013 |
| 抄録: | Time-sequence data is high dimensional and contains a lot of information, which can be utilized in various fields, such as insurance, finance, and advertising. Personal data including time-sequence data is converted to anonymized datasets, which need to strike a balance between both privacy and utility. In this paper, we consider low-rank matrix factorization as one of anonymization methods and evaluate its efficiency. We convert time-sequence datasets to matrices and evaluate both privacy and utility. The record IDs in time-sequence data are changed at regular intervals to reduce re-identification risk. However, since individuals tend to behave in a similar fashion over periods of time, there remains a risk of record linkage even if record IDs are different. Hence, we evaluate the re-identification and linkage risks as privacy risks of time-sequence data. Our experimental results show that matrix factorization is a viable anonymization method and it can achieve better utility than existing anonymization methods. |
| Rights: | Copyright (C)2020 IEICE. Tomoaki Mimoto, Seira Hidano, Shinsaku Kiyomoto, and Atsuko Miyaji, IEICE Transactions on Information and Systems, E103-D(2), 2020, 299-308. https://www.ieice.org/jpn/trans_online/ |
| URI: | http://hdl.handle.net/10119/16235 |
| 資料タイプ: | publisher |
| 出現コレクション: | b10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| 3073.pdf | | 1083Kb | Adobe PDF | 見る/開く |
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