| 書目名稱 | Privacy-Preserving Data Publishing | | 編輯 | Raymond Chi-Wing Wong,Ada Wai-Chee Fu | | 視頻video | http://file.papertrans.cn/757/756069/756069.mp4 | | 叢書名稱 | Synthesis Lectures on Data Management | | 圖書封面 |  | | 描述 | Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical data, sensitive information can be the fact that a particular patient suffers from HIV. In spatial data, sensitive information can be a specific location of an individual. In web surfing data, the information that a user browses certain websites may be considered sensitive. Consider a dataset containing some sensitive information is to be released to the public. In order to protect sensitive information, the simplest solution is not to disclose the information. However, this would be an overkill since it will hinder the process of data analysis over the data from which we can find interesting patterns. Moreover, in some applications, the data must be disclosed under the government regulations. Alternatively, the data owner can first modify the data such that the modified data can guarantee privacy and, at the same time, the modified data retains sufficient utility and can be released to | | 出版日期 | Book 2010 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01834-3 | | isbn_softcover | 978-3-031-00706-4 | | isbn_ebook | 978-3-031-01834-3Series ISSN 2153-5418 Series E-ISSN 2153-5426 | | issn_series | 2153-5418 | | copyright | Springer Nature Switzerland AG 2010 |
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