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In response to the growing interest in genome-wide association study (GWAS) data privacy, the Integrating Data for Analysis, Anonymization and SHaring (iDASH) center organized the iDASH Healthcare Privacy Protection Challenge, with the aim of investigating the effectiveness of applying privacy-preserving methodologies to human genetic data. This paper is(More)
The objective of machine learning is to extract useful information from data, while privacy is preserved by concealing information. Thus it seems hard to reconcile these competing interests. However, they frequently must be balanced when mining sensitive data. For example, medical research represents an important application where it is necessary both to(More)
Recent advances in click modeling have established it as an attractive approach to interpret search click data. These advances characterize users' search behavior either in advertisement blocks, or within an organic search block through probabilistic models. Yet, when searching for information on a search result page, one is often interacting with the(More)
Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods(More)
A reasonable compromise of privacy and utility exists at an "appropriate" resolution of the data. We proposed novel mechanisms to achieve privacy preserving data publishing (PPDP) satisfying ε-differential privacy with improved utility through component analysis. The mechanisms studied in this article are Principal Component Analysis (PCA) and Linear(More)
OBJECTIVE The Cox proportional hazards model is a widely used method for analyzing survival data. To achieve sufficient statistical power in a survival analysis, it usually requires a large amount of data. Data sharing across institutions could be a potential workaround for providing this added power. METHODS AND MATERIALS The authors develop a web(More)
As data privacy researchers, we appreciate the opportunity to comment on the Advance Notice of Proposed Rulemaking (ANPRM) on human subjects research protections that appeared in 76 Federal Register 44512 (July 26, 2011). These comments mostly address the fitness of HIPAA provisions in privacy issues raised by the ANPRM. Data privacy is emerging as a field,(More)