Differential Privacy for Dynamic Data by Jerome Le Ny
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.-
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Jerome Le Ny is currently an Associate Professor in the Department of Electrical Engineering at Polytechnique Montreal, which he joined in May 2012, and a member of GERAD, a Canadian multi-university research center for decision systems. His research interests include control theory and stochastic signal processing, privacy and security for cyber-physical systems, and the design of large-scale intelligent automation, with applications to transportation systems, energy systems, and distributed robotics in particular. He has published papers on the topic of privacy-preserving dynamic data analysis since 2012 and co-organized invited sessions on the topic of privacy in systems and control at several Conference on Decision and Control (CDC) since then. He participated in a tutorial session on this topic at the CDC 2016. His group has received several research awards, including a best student paper award at CDC 2016, and a fellowship from the Humboldt Foundation in 2018.
| SKU | Unavailable |
| ISBN 13 | 9783030410384 |
| ISBN 10 | 3030410382 |
| Title | Differential Privacy for Dynamic Data |
| Author | Jerome Le Ny |
| Series | Springerbriefs In Electrical And Computer Engineering Ser |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2020-03-25 |
| Number of pages | 110 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |