Description
The goal of this project is to develop new concepts and frameworks for
privacy in collaborative environments, focusing on global properties
of the joint dataset such as security against unreasonable searches and
abusive information harvesting. Techniques include provably secure data
transformations that assure global and individual privacy properties
after information has been released in response to a legitimate request.
To enforce global privacy policies, this project will develop new
cryptographic techniques for dataset obfuscation and sanitization,
ensuring that only policy-compliant queries can be computed on the dataset
after it has been transferred to the collaborators. The main objective is
to design privacy-preserving data transformations that are provably secure
without unrealistic assumptions about "tamper-proof" software or hardware.
This project is supported by the NSF grants
IIS-0534198 and
IIS-0534052
(Jan 1, 2006 - Dec 31, 2009).
People
Publications
- A. Johnson.
Design and Analysis of Efficient Anonymous-Communication
Protocols.
PhD Thesis, Computer Science Department, Yale University, 2009.
- J. Feigenbaum, A. Jaggard, and M. Schapira.
Approximate Privacy:
Foundations and Quantification.
DIMACS Technical Report 2009-14, Rutgers University, 2009.
- A. Narayanan and V. Shmatikov.
De-anonymizing Social Networks.
30th IEEE Symposium on Security and Privacy, 2009.
- J. Brickell and V. Shmatikov.
Privacy-Preserving Classifier Learning.
13th International Conference on Financial Cryptography and
and Data Security, 2009.
- J. Feigenbaum, D. Parkes, and D. Pennock.
Computational Challenges in E-Commerce.
Communications of the ACM, 2009.
- J. Brickell and V. Shmatikov.
The Cost of Privacy:
Destruction of Data-Mining Utility in Anonymized Data Publishing.
14th ACM SIGKDD International Conference on Knowledge Discovery
and Data Mining (KDD), 2008.
- D. Weitzner et al.
Information Accountability.
Communications of the ACM, 2008.
- A. Narayanan and V. Shmatikov.
Robust De-anonymization of Large Sparse Datasets.
29th IEEE Symposium on Security and Privacy, 2008.
- S. Jha, L. Kruger, and V. Shmatikov.
Towards Practical Privacy for Genomic Computation.
29th IEEE Symposium on Security and Privacy, 2008.
- J. Brickell, D. Porter, V. Shmatikov, and E. Witchel.
Privacy-Preserving Remote Diagnostics.
14th ACM Conference on Computer and Communications Security
(CCS), 2007.
- F. Saint-Jean, A. Johnson, D. Boneh, and J. Feigenbaum.
Private Web Search.
ACM Workshop on Privacy in Electronic Society (WPES), 2007.
- J. Feigenbaum, A. Johnson, and P. Syverson.
Probabilistic Analysis of Onion Routing in a Black-Box Model.
ACM Workshop on Privacy in Electronic Society (WPES), 2007.
- V. Shmatikov and M-H. Wang.
Security Against Probe-Response Attacks in Collaborative
Intrusion Detection.
ACM SIGCOMM Workshop on Large-Scale Attack Defense (LSAD),
2007.
- S. Jarecki and V. Shmatikov.
Efficient Two-Party Secure Computation on Committed Inputs.
Advances in Cryptology - EUROCRYPT, 2007.
- J. Brickell and V. Shmatikov.
Efficient Anonymity-Preserving Data Collection.
12th ACM SIGKDD International Conference on Knowledge Discovery
and Data Mining (KDD), 2006.
- J. Zhang and J. Feigenbaum.
Finding Highly Correlated Pairs Efficiently with Powerful Pruning.
15th ACM Conference on Information and Knowledge Management
(CIKM), 2006.
- J. Feigenbaum and D. Weitzner (eds.).
Report on the 2006 PORTIA/TAMI Workshop on Privacy and Accountability.
- P. Porras and V. Shmatikov.
Large-Scale Collection and Sanitization of Network Security Data:
Risks and Challenges.
New Security Paradigms Workshop, 2006.
- J. Brickell and V. Shmatikov.
Privacy-Preserving Graph Algorithms in the Semi-Honest Model.
Advances in Cryptology - ASIACRYPT 2005.
- A. Narayanan and V. Shmatikov.
Obfuscated Databases and Group Privacy.
12th ACM Conference on Computer and Communications Security
(CCS), 2005.
Contact: shmat AT cs DOT utexas DOT edu