https://grants.nih.gov/grants/guide/notice-files/NOT-OD-25-081.html
Posts Tagged ‘privacy’
NOT-OD-25-081: Protecting Human Genomic Data when Developing Generative Artificial Intelligence Tools and Applications
November 8, 2025Kristin Cabot Resigns as Astronomer’s Chief People Officer After Coldplay Incident – The New York Times
August 1, 2025Astronomer CEO Andy Byron Placed on Leave After Video at Coldplay Concert Exposes Alleged Affair – The New York Times
July 30, 2025The Algorithmic Foundations of Differential Privacy
July 14, 2025https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf
The Algorithmic Foundations of Differential Privacy
Cynthia Dwork
Microsoft Research, USA
Aaron Roth
University of Pennsylvania, USA
Foundations and Trends in Theoretical Computer Science, NOW Publishers. 2014.
Humans have nasal respiratory fingerprints: Current Biology
July 13, 2025https://www.cell.com/current-biology/fulltext/S0960-9822(25)00583-4
Soroka, T., Ravia, A., Snitz, K., Honigstein, D., Weissbrod, A., Gorodisky, L., Weiss, T., Perl, O., & Sobel, N. (2025). Humans have nasal respiratory fingerprints. Current Biology.
https://doi.org/10.1016/j.cub.2025.05.008
geneinfosec
July 6, 2025The Limits of Differential Privacy (and Its Misuse in Data Release and Machine Learning) | July 2021 | Communications of the ACM
June 28, 2025Differential privacy is not a silver bullet for all privacy problems. By Josep Domingo-Ferrer, David Sánchez, and Alberto Blanco-Justicia Posted Jul 1 2021
QT:{{”
The traditional approach to statistical disclosure control (SDC) for privacy protection is utility-first. Since the 1970s, national statistical institutes have been using anonymization methods with heuristic parameter choice and suitable utility preservation properties to protect data before release. Their goal is to publish analytically useful data that cannot be linked to specific respondents or leak confidential information on them.
In the late 1990s, the computer science community took another angle and proposed privacy-first data protection. In this approach a privacy model specifying an ex ante privacy condition is enforced using one or several SDC methods, such as noise addition, generalization, or microaggregation. The parameters of the SDC methods depend on the privacy model parameters, and too strict a choice of the latter may result in poor utility. The first widely accepted privacy model was k-anonymity, whereas differential privacy (DP) is the model that currently attracts the most attention.
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