This workshop is jointly sponsored by:
Monday, February 4, 2008
8:00 - 8:50 Breakfast and Registration
8:50 - 9:00 Welcome and Opening remarks
Rebecca Wright, DIMACS Deputy Director
Sharon Regev, Consulate General of Israel
Kobbi Nissim and Benny Pinkas, Workshop Organizers
9:00 - 10:00 Tutorial: Differential Privacy
Adam Smith, Penn State University
10:00 - 10:30 PINQ
Frank McSherry, Microsoft
10:30 - 11:00 Break
11:00 - 12:00 Tutorial: Smooth Sensitivity and Sampling
Sofya Raskhodnikova, Penn State University
12:00 - 12:30 Tutorial: Exponential Mechanism
Kunal Talwar, Microsoft
12:30 - 2:00 Lunch
2:00 - 3:00 Tutorial: Statistical Disclosure Limitation Methods
Alexandra Slavkovic, Penn State University
3:00 - 3:30 Break
3:30 - 4:30 Tutorial: Synthetic Data
John Abowd, Cornell University
Tuesday, February 5, 2008
8:30 - 9:00 Breakfast and Registration
9:00 - 10:30 Tutorial: Secure Multiparty Computation and
Privacy-Preserving Data Mining
Yehuda Lindell, Bar Ilan University
10:30 - 11:00 Break
11:00 - 11:35 On the Difficulties of Achieving Disclosure Prevention
Moni Naor, Weizmann Institute of Science
11:35 - 12:05 E Gov, Online Citizen Scrutiny and Participation -
The Joint Challenges for Cryptologists and Policy Makers
Tal Zarsky, University of Haifa
12:05 - 12:30 Cyber Sovereignty
David Chaum
12:30 - 2:00 Lunch
2:00 - 2:25 Privacy: Theory Meets Practice on the Map
John Abowd, Cornell University
2:25 - 2:50 A Hybrid Perturbation/Swapping Approach for Masking Numerical Data
Rathindra Sarathy, Oklahoma State University
2:50 - 3:20 Break
3:20 - 3:45 Deterministic History-Independent Strategies for Storing
Information on Write-Once Memories
Gil Segev, Weizmann Institute of Science
3:45 - 4:10 Cell Suppressions Leak Information
Shubha Nabar, Stanford University
4:10 - 4:35 A Learning Theory Perspective on Data Privacy:
New Hope for Releasing Useful Databases Privately
Avrim Blum, Katrina Ligett, Aaron Roth, Carnegie Mellon University
4:50 - 5:50 Distinguished Lecture: Dilemmas of Privacy
Problems of Marketers, Governments and Social Advocates
Joseph Turow, University of Pennsylvania
5:50 Dinner
Wednesday, February 6, 2008
8:30 - 9:00 Breakfast and Registration
9:00 - 9:30 What Can We Learn Privately?
Shiva Kasiviswanathan
9:30 - 10:00 Mechanism Design
Frank McSherry / Kunal Talwar
10:00 - 10:30 Everlasting Privacy in Voting Protocols
Tal Moran, The Weizmann Institute of Science
10:30 - 11:00 Break
11:00 - 11:30 Efficient Protocols for Set Intersection and Pattern Matching
with Security Against Malicious and Covert Adversaries
Carmit Hazay, Bar-Ilan University
11:30 - 12:00 How to Collect a Function Securely?
Aggelos Kiayias, University of Connecticut
12:00 - 12:30 On the Cultural Inflections of Surveillance Discourse
Rivka Ribak, University of Haifa
12:30 - 2:00 Lunch
2:00 - 2:25 Efficient Signature Schemes Supporting Sedaction,
Pseudonymization, and Data Deidentification
Daphne Yao, Rutgers University
2:25 - 2:50 Robust De-anonymization of Multi-dimensional Databases
Vitaly Shmatikov, The University of Texas at Austin
2:50 - 3:20 Break
3:20 - 3:45 Constructions of Truly Practical Secure
Protocols using Standard Smartcards
Yehuda Lindell, Bar Ilan University
3:45 - 4:10 Distributed Private Data Analysis: Simultaneously Solving How and What
Eran Omri, Ben Gurion University
4:10 - 4:35 Delegatable Anonymous Credentials
Melissa Chase
Thursday, February 7, 2008
8:30 - 9:00 Breakfast and Registration
9:00 - 9:25 Protecting the Confidentiality of Tables by Adding Noise to
the Underlying Microdata
Paul B. Massell, Statistical Research Division, U.S. Census Bureau
9:25 - 9:50 How Should We Solve Search Problems Privately?
Amos Beimel, Ben-Gurion University
9:50 - 10:15 Deniable Authentication
Yevgeniy Dodis, NYU and Harvard University
10:15 - 10:30 Alex Selkirk, The Common Datatrust Foundation
10:30 - 10:45 Break
10:45 - 11:30 Helen Nissenbaum
11:30 - 12:30 PANEL
Moderated by Stephen Fienberg
12:30 - 2:00 Lunch
2:00 - 2:25 Privacy Utility Tradeoff in Data Publishing
Vibhor Rastogi, University of Washington
2:25 - 2:50 On Lower Bounds for Noise in Private Analysis of Statistical Databases
Sergey Yekhanin, Institute for Advanced Study
2:50 - 3:20 Break
3:20 - 3:45 k-Anonymous Data Mining
Arik Friedman, Technion, Israel
3:45 - 4:10 Efficient Algorithms for Masking and Finding Quasi-identifiers
Ying Xu, Stanford University
4:10 - 4:35 Privacy-Preserving Sharing of Network Data with Anonymization Tools: -
Characterizing Privacy/Utility Tradeoffs and Multi-Level Protection
William Yurcik, University of Texas at Dallas
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