DIMACS/PORTIA Workshop on Privacy-Preserving Data Mining

March 15 - 16, 2004
DIMACS Center, CoRE Building, Rutgers University, Piscataway, NJ

Organizers:
Cynthia Dwork, Microsoft, dwork at microsoft.com
Benny Pinkas, HP Labs, benny.pinkas at hp.com
Rebecca Wright, Stevens Institute of Technology, rwright at cs.stevens-tech.edu
Presented under the auspices of the Special Focus on Communication Security and Information Privacy, and the PORTIA project.

The workshop is followed by a related working group on March 17, 2004.

Workshop Program:


Monday, March 15, 2004

 8:00 -  8:50  Registration -  1st Floor Lobby, CoRE Building
               Breakfast - 4th Floor, Lounge, CoRE Building

 8:50 -  9:00  Welcome and Opening Remarks
               Mel Janowitz, DIMACS Associate Director

 9:00 -  9:30  From Idiosyncratic to Stereotypical: Toward
               Privacy in Public Databases
               Shuchi Chawla, CMU

 9:30 - 10:00  Privacy-Preserving Datamining on Vertically Partitioned Databases
               Kobbi Nissim, Microsoft Research

10:00 - 10:40  Confidentiality in Tables Viewed from an Algebraic Perspective
               Lawrence H. Cox, CDC

10:40 - 11:10  Break - 4th Floor, Lounge, CoRE Building

11:10 - 11:40  Privacy Preserving Computation of the k'th Ranked Element 
               Gagan Aggarwal, Stanford University

11:40 - 12:10  Efficient Private Matching and Set Intersection 
               Mike Freedman, NYU 

12:10 - 12:30  An Experimental Study of Association Rule Hiding Techniques
               Emmanuel Pontikakis, University of Patras

12:30 -  2:00  Lunch - 4th Floor, Lounge, CoRE Building

 2:00 -  2:15  Public-Key Encryption with Keyword Search
               Giovanni DiCrescenzo, Telcordia

 2:15 -  2:30  Privacy-Enhanced Searches Using Encrypted Bloom Filters
               Steve Bellovin, AT & T Research 

 2:30 -  2:45  Secure indexes
               Eu-Jin Goh, Stanford University 

 2:45 -  3:00  Privacy Preserving Keyword Searches on Remote Encrypted Data
               Yan-Cheng Chang, Harvard University

 3:00 -  3:30  Completeness in Two-Party Secure Computation - A Computational View
               Moni Naor, Weizmann Institute

 3:30 -  4:00  Break - 4th Floor, Lounge, CoRE Building

 4:00 -  4:40  Data Mining and Information Privacy - 
               New Problems and the Search For Solutions 
               Tal Zarsky, Yale University

 4:40 -  5:10  On the Difficulty of Defining Ideal Functionalities for Privacy 
               Preserving Data Mining: Why naive Secure Multiparty Computation Fails
               Yehuda Lindell, IBM

 5:20 -  7:00  Wine and Cheese Reception - DIMACS Lounge

Tuesday, March 16, 2004

 8:30 -  9:00  Registration -  1st Floor Lobby, CoRE Building
               Breakfast - 4th Floor, Lounge, CoRE Building

 9:00 -  9:30  Extending Oblivious Transfers Efficiently
               Yuval Ishai, Technion

 9:30 - 10:00  Amortized PIR via Batch Codes
               Eyal Kushilevitz, Technion

10:00 - 10:20  Private Inference Control 
               David Woodruff, MIT

10:20 - 10:40  Cryptographic Randomized Response Techniques
               Markus Jakobsson, RSA Security 

10:40 - 11:10  Break - 4th Floor, Lounge, CoRE Building

11:10 - 11:50  Privacy as Contextual Integrity
               Helen Nissenbaum, NYU

11:50 - 12:20  Trading Entropy for Privacy, or Unconditional Security
               When Information Leakage is Unavoidable 
               Adam Smith, MIT

11:20 - 12:40  Calypso: UCSD's Project on Privacy in Database Publishing
               Alin Deutsch, UCSD 

12:40 -  2:10  Lunch - 4th Floor, Lounge, CoRE Building

 2:10 -  2:30  When can the randomization fail to protect privacy?
               Kevin Du, Syracuse University

 2:30 -  2:50  Computing sketches of matrices efficiently and
               applications to privacy preserving data mining 
               Petros Drineas, Rensselaer Polytechnic Institute

 2:50 -  3:10  Information leakage and privacy in data mining
               Poorvi Vora, GWU 

 3:10 -  3:30  Random Encodings, Privacy Loss, and Some Possible Solutions: 
               A Coding Theory Perspective 
               Hillol Kargupta, University of Maryland 

 3:30 -  4:00  Break - 4th Floor, Lounge, CoRE Building

 4:00 -  4:40  Secure Regression on Distributed Databases
               Alan Karr, National Institute of Statistical Sciences

 4:40 -  5:00  Tabular Data: Releases of Conditionals and Marginals
               Aleksandra Slavkovic, Carnegie Mellon University

 5:00 -  5:30  Private data mining based on randomized linear projections
               Martin Strauss, AT&T Research
Previous: Participation
Next: Registration
Workshop Index
DIMACS Homepage
Contacting the Center
Document last modified on August 12, 2004.