| Differential Privacy and Applications 2017 Edition Contributor(s): Zhu, Tianqing (Author), Li, Gang (Author), Zhou, Wanlei (Author) |
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ISBN: 3319620029 ISBN-13: 9783319620022 Publisher: Springer OUR PRICE: $161.49 Product Type: Hardcover - Other Formats Published: September 2017 |
| Additional Information |
| BISAC Categories: - Computers | Databases - Data Mining - Computers | Security - Online Safety & Privacy - Computers | Intelligence (ai) & Semantics |
| Dewey: 005.8 |
| Series: Advances in Information Security |
| Physical Information: 0.63" H x 6.14" W x 9.21" (1.17 lbs) 235 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: This book focuses on differential privacy and its application with an emphasis on technical and application aspects. This book also presents the most recent research on differential privacy with a theory perspective. It provides an approachable strategy for researchers and engineers to implement differential privacy in real world applications. Early chapters are focused on two major directions, differentially private data publishing and differentially private data analysis. Data publishing focuses on how to modify the original dataset or the queries with the guarantee of differential privacy. Privacy data analysis concentrates on how to modify the data analysis algorithm to satisfy differential privacy, while retaining a high mining accuracy. The authors also introduce several applications in real world applications, including recommender systems and location privacy Advanced level students in computer science and engineering, as well as researchers and professionals working in privacy preserving, data mining, machine learning and data analysis will find this book useful as a reference. Engineers in database, network security, social networks and web services will also find this book useful. |