Practical data-swapping: the first steps
ACM Transactions on Database Systems (TODS)
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
The statistical security of a statistical database
ACM Transactions on Database Systems (TODS)
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Practical Data-Oriented Microaggregation for Statistical Disclosure Control
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Impacts of user privacy preferences on personalized systems: a comparative study
Designing personalized user experiences in eCommerce
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data
Information Systems Research
Fuzzy based clustering algorithm for privacy preserving data mining
International Journal of Business Information Systems
Strategic information system design practices in an emerging economy
International Journal of Business Information Systems
Information system development approach: facts from IT SMEs in India
International Journal of Business Information Systems
Protecting Privacy Against Record Linkage Disclosure: A Bounded Swapping Approach for Numeric Data
Information Systems Research
Maturity models for management of information systems and technologies in healthcare
International Journal of Business Information Systems
Decentralised privacy preservation in social networks
International Journal of Business Information Systems
Vendor managed inventory via SOA in healthcare supply chain management
International Journal of Business Information Systems
The rationale of e-health evaluation: the case of NHS Direct
International Journal of Business Information Systems
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The extensive use of electronic healthcare data has increased privacy concerns. While most healthcare organisations are conscientious in protecting their data in their databases, very few organisations take enough precautions to protect data that is shared with known third party organisations. Recently the regulatory environment has tightened the laws to enforce privacy protection. The goal of this research is to explore the application of data masking solutions for protecting patient privacy when data is shared with external organisations for research, analysis and other similar purposes. Specifically, this research project develops a system that protects data without removing sensitive attributes. Our application allows high quality data analysis with the masked data. Dataset-level properties and statistics remain approximately the same after data masking; however, individual record-level values are altered to prevent privacy disclosure. A pilot evaluation study on large real-world healthcare data shows the effectiveness of our solution in privacy protection.