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Commercial Data Privacy and Innovation in the Internet Economy: A Dynamic Policy Framework

Department of Commerce Internet Policy Task Force

Protecting Consumer Privacy in an Era of Rapid Change–A Proposed Framework for Businesses and Policymakers

FTC Staff

Consumer Data Privacy in a Networked World: A Framework for Protecting Privacy and Promoting Innovation in the Global Digital Economy

A. Anonymous

An Axiomatic View of Statistical Privacy and Utility

Daniel Kifer, Bing-Rong Lin

Differential Privacy in Practice: Expose your Epsilons!

Cynthia Dwork, Nitin Kohli, Deirdre Mulligan

Heterogeneous Differential Privacy

Mohammad Alaggan, Sébastien Gambs, Anne-Marie Kermarrec

How Uncertainty about Privacy and Confidentiality is Hampering Efforts to More Effectively Use Administrative Records in Producing U.S. National Statistics

Gerald W. Gates

Gradual Release of Sensitive Data under Differential Privacy

Fragkiskos Koufogiannis, Shuo Han, George J. Pappas

Differentially Private Confidence Intervals for Empirical Risk Minimization

Yue Wang, Daniel Kifer, Jaewoo Lee

Towards a Systematic Analysis of Privacy Definitions

Bing-Rong Lin, Dan Kifer

BLENDER: Enabling Local Search with a Hybrid Differential Privacy Model

Brendan Avent, Aleksandra Korolova, David Zeber, Torgeir Hovden, Benjamin Livshits

Per-instance Differential Privacy

Yu-Xiang Wang

Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM

Steven Wu, Aaron Roth, Katrina Ligett, Bo Waggoner, Seth Neel

Statistical Déjà Vu: The National Data Center Proposal of 1965 and Its Descendants

Rebecca Kraus

Calibrating Noise to Sensitivity in Private Data Analysis

Cynthia Dwork, Frank McSherry, Kobbi Nissim, Adam Smith

17-51

Federal Statistical Confidentiality and Business Data: Twentieth Century Challenges and Continuing Issues

Margo J. Anderson, William Seltzer

Privacy via the Johnson-Lindenstrauss Transform

Krishnaram Kenthapadi, Aleksandra Korolova, Ilya Mironov, Nina Mishra

An Evaluation Framework for Privacy-Preserving Record Linkage

Dinusha Vatsalan, Peter Christen, Christine M. O'Keefe, Vassilios S. Verykios

A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples

Raj Chetty, John N Friedman

Differential Privacy for Statistics: What we Know and What we Want to Learn

Cynthia Dwork, Adam Smith

Silent Listeners: The Evolution of Privacy and Disclosure on Facebook

Fred Stutzman, Ralph Gross, Alessandro Acquisti

Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning

Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft

Local Differential Privacy for Evolving Data

Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner

Differential Privacy on Finite Computers

Victor Balcer, Salil Vadhan

On the 'Semantics' of Differential Privacy: A Bayesian Formulation

Shiva P. Kasiviswanathan, Adam Smith
1 - 25 of 133 items 1 2 3 4 5 6 > >> 

about2

The Journal of Privacy and Confidentiality is an open-access multi-disciplinary journal whose purpose is to facilitate the coalescence of research methodologies and activities in the areas of privacy, confidentiality, and disclosure limitation. The JPC seeks to publish a wide range of research and review papers, not only from academia, but also from government (especially official statistical agencies) and industry, and to serve as a forum for exchange of views, discussion, and news. For more information, see the About the Journal page.

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