Differential Privacy for Dynamic Data is popular PDF and ePub book, written by Jerome Le Ny in 2020-03-24, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Differential Privacy for Dynamic Data can be Read Online from any device for your convenience.
Differential Privacy for Dynamic Data Book PDF Summary
This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.
Detail Book of Differential Privacy for Dynamic Data PDF
- Author : Jerome Le Ny
- Release : 24 March 2020
- Publisher : Springer Nature
- ISBN : 9783030410391
- Genre : Technology & Engineering
- Total Page : 118 pages
- Language : English
- PDF File Size : 12,5 Mb
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