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- When do Data Mining Results Violate Privacy? Murat Kantarcioglu
- Incentive Compatible Privacy-Preserving Data Murat Kantarcioglu, U. of Texas at Dallas, muratk@utdallas.edu
- Sovereign Joins Rakesh Agrawal
- Incentive Compatible Distributed Data Mining Murat Kantarcioglu and Robert Nix
- Security Issues in Querying Encrypted Data Murat Kantarcioglu1
- Inferring Private Information Using Social Network Data Jack Lindamood
- Privacy-Preserving Decision Trees over Vertically Partitioned Data
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- The applicability of the perturbation based privacy preserving data mining for real-world data
- Transforming semi-honest protocols to ensure accountability Wei Jiang a,*, Chris Clifton a
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- Privacy-Preserving Distributed Mining of Association Rules
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- A Semantic Web Based Framework for Social Network Access Control
- An Efficient Approximate Protocol for Privacy-Preserving Association Rule Mining
- Privacy Preserving Decision Tree Mining from Perturbed Data Global Information Security
- Incentive and Trust Issues in Assured Information Ryan Layfield, Murat Kantarcioglu, and Bhavani Thuraisingham
- A Privacy-Preserving Framework for Integrating Person-Specific Databases
- A Hybrid Approach to Private Record Linkage Ali Inan #1*, Murat Kantarcioglu #2*, Elisa Bertino t3*, Monica Scannapieco 4
- Design and Analysis of Querying Encrypted Data in Relational Databases
- Preventing Private Information Inference Attacks on Social Networks
- Inferring Private Information Using Social Network Data
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- Formal anonymity models for efficient privacy-preserving joins Murat Kantarcioglu a,*, Ali Inan a
