Privacy-Preserving Algorithms: The Gain and the Loss
Individual Privacy vs. Population Information
The rapid development of Big Data technology has put privacy issues into focus. Data-driven technologies help people make appropriate inferences and decisions, but the large amount of data collected by data curators contains sensitive personal information, such as browsing history, personal conversations, and medical records. As more technologies and data analysis results are made available to interested parties, it becomes increasingly urgent to design algorithms that can protect individual privacy, while still being able to draw useful information about the population from the data.
Some content is only viewable by ASA Members. Please login or become an ASA member to gain access.
Hi Sue,
Email ASA customer service at asainfo@amstat.org to order a specific issue or article. To gain access to all the articles, you can become a member of the ASA https://www.amstat.org/asa/membership/home.aspx?hkey=f7211093-c758-4f60-9569-35bff9348415
How can I purchase a copy of this specific Chance magazine or gain access to all the articles?
Thanks for your help, Sue