Differential privacy has emerged as an important standard for privacy preserving computation over databases containing sensitive information about individuals. Research …
Differential privacy is at a turning point. Implementations have been successfully leveraged in private industry, the public sector, and academia in a wide variety of applications, allowing …
Over the last decade, differential privacy (DP) has emerged as the de facto standard privacy notion for research in privacy-preserving data analysis and publishing. The DP notion offers …
Corporations, organizations, and governments have collected, digitized, and stored information in digital forms since the invention of computers, and the speed of such data …
SL Garfinkel, JM Abowd, S Powazek - … of the 2018 Workshop on Privacy …, 2018 - dl.acm.org
When differential privacy was created more than a decade ago, the motivating example was statistics published by an official statistics agency. In attempting to transition differential …
FK Dankar, K El Emam - Proceedings of the 2012 Joint EDBT/ICDT …, 2012 - dl.acm.org
Differential privacy has gained a lot of attention in recent years as a general model for the protection of personal information when used and disclosed for secondary purposes. It has …
Differential privacy is a popular privacy model within the research community because of the strong privacy guarantee it offers, namely that the presence or absence of any individual in a …
Differential privacy is becoming a gold standard notion of privacy; it offers a guaranteed bound on loss of privacy due to release of query results, even under worst-case …
S Vadhan - Tutorials on the Foundations of Cryptography …, 2017 - Springer
Differential privacy is a theoretical framework for ensuring the privacy of individual-level data when performing statistical analysis of privacy-sensitive datasets. This tutorial provides an …