Handbook of sharing confidential data : differential privacy, secure multiparty computation, and synthetic data
著者
書誌事項
Handbook of sharing confidential data : differential privacy, secure multiparty computation, and synthetic data
（Handbooks of modern statistical methods / Series editors, Garrett Fitzmaurice）
CRC Press, 2025
- : hbk
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Content Type: text (ncrcontent), Media Type: unmediated (ncrmedia), Carrier Type: volume (ncrcarrier)
Other editors: Daniel Kifer, Jerome Reiter and Aleksandra Slavković
"A Chapman & Hall Book"--Title page
Includes bibliographical references and index.
Summary:"Statistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects' and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature-specifically, synthetic data, formal privacy, and secure computation-can be used to manage trade-offs in disclosure risk and data usefulness."--Back cover
