Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Executing SQL over encrypted data in the database-service-provider model
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Datafly: A System for Providing Anonymity in Medical Data
Proceedings of the IFIP TC11 WG11.3 Eleventh International Conference on Database Securty XI: Status and Prospects
Query-preserving watermarking of relational databases and XML documents
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Transforming data to satisfy privacy constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Winnowing: local algorithms for document fingerprinting
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Rights protection for relational data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Constructing a virtual primary key for fingerprinting relational data
Proceedings of the 3rd ACM workshop on Digital rights management
Proving Ownership over Categorical Data
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Chip-secured data access: confidential data on untrusted servers
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Watermarking relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Controlling access to published data using cryptography
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Privacy-preserving indexing of documents on the network
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
IWDW'02 Proceedings of the 1st international conference on Digital watermarking
A novel approach for privacy-preserving video sharing
Proceedings of the 14th ACM international conference on Information and knowledge management
Cryptographic alias e-mail addresses for privacy enforcement in business outsourcing
Proceedings of the 2005 workshop on Digital identity management
Publicly verifiable ownership protection for relational databases
ASIACCS '06 Proceedings of the 2006 ACM Symposium on Information, computer and communications security
Privacy leakage in multi-relational databases: a semi-supervised learning perspective
The VLDB Journal — The International Journal on Very Large Data Bases
Mining multiple private databases using a kNN classifier
Proceedings of the 2007 ACM symposium on Applied computing
Preserving data privacy in outsourcing data aggregation services
ACM Transactions on Internet Technology (TOIT) - Special Issue on the Internet and Outsourcing
Time series compressibility and privacy
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Providing k-anonymity in data mining
The VLDB Journal — The International Journal on Very Large Data Bases
Does enforcing anonymity mean decreasing data usefulness?
Proceedings of the 4th ACM workshop on Quality of protection
Towards privacy-preserving integration of distributed heterogeneous data
Proceedings of the 2nd PhD workshop on Information and knowledge management
HIDE: heterogeneous information DE-identification
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Embedding and Retrieving Private Metadata in Electrocardiograms
Journal of Medical Systems
Privacy-Preserving Computation and Verification of Aggregate Queries on Outsourced Databases
PETS '09 Proceedings of the 9th International Symposium on Privacy Enhancing Technologies
An integrated framework for de-identifying unstructured medical data
Data & Knowledge Engineering
Threat analysis of online health information system
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Learning latent variable models from distributed and abstracted data
Information Sciences: an International Journal
Privacy-aware DaaS services composition
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Rights protection for data cubes
ISC'06 Proceedings of the 9th international conference on Information Security
Preserving user location privacy in mobile data management infrastructures
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
Subset selection approach for watermarking relational databases
ICDEM'10 Proceedings of the Second international conference on Data Engineering and Management
Policy-Enhanced private set intersection: sharing information while enforcing privacy policies
PKC'12 Proceedings of the 15th international conference on Practice and Theory in Public Key Cryptography
Enabling robust information accountability in E-healthcare systems
HealthSec'12 Proceedings of the 3rd USENIX conference on Health Security and Privacy
Dividing secrets to secure data outsourcing
Information Sciences: an International Journal
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The demand for the secondary use of medical data is increasing steadily to allow for the provision of better quality health care. Two important issues pertaining to this sharing of data have to be addressed: one is the privacy protection for individuals referred to in the data; the other is copyright protection over the data. In this paper, we present a unified framework that seamlessly combines techniques of binning and digital watermarking to attain the dual goals of privacy and copyright protection. Our binning method is built upon an earlier approach of generalization and suppression by allowing a broader concept of generalization. To ensure data usefulness, we propose constraining Binning by usage metrics that define maximal allowable information loss, and the metrics can be enforced off-line. Our watermarking algorithm watermarks the binned data in a hierarchical manner by leveraging on the very nature of the data. The method is resilient to the generalization attack that is specific to the binned data, as well as other attacks intended to destroy the inserted mark. We prove that watermarking could not adversely interfere with binning, and implemented the framework. Experiments were conducted, and the results show the robustness of the proposed framework.