2011 DifferentiallyPrivateDataReleas

• (Mohammed et al., 2011) ⇒ Noman Mohammed, Rui Chen, Benjamin C.M. Fung, and Philip S. Yu. (2011). “Differentially Private Data Release for Data Mining.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011) Journal. ISBN:978-1-4503-0813-7 doi:10.1145/2020408.2020487

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222011%22+Differentially+Private+Data+Release+for+Data+Mining
• http://dl.acm.org/citation.cfm?id=2020408.2020487&preflayout=flat#citedby

Quotes

Author Keywords

• Algorithms; anonymization; data mining; data mining; differential privacy; performance; security; security, integrity, and protection

Abstract

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among the existing privacy models, ∈-differential privacy provides one of the strongest privacy guarantees and has no assumptions about an adversary's background knowledge. Most of the existing solutions that ensure ∈-differential privacy are based on an interactive model, where the data miner is only allowed to pose aggregate queries to the database. In this paper, we propose the first anonymization algorithm for the non-interactive setting based on the generalization technique. The proposed solution first probabilistically generalizes the raw data and then adds noise to guarantee ∈-differential privacy. As a sample application, we show that the anonymized data can be used effectively to build a decision tree induction classifier. Experimental results demonstrate that the proposed non-interactive anonymization algorithm is scalable and performs better than the existing solutions for classification analysis.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 DifferentiallyPrivateDataReleas	Philip S. Yu Noman Mohammed Benjamin C.M. Fung Rui Chen			Differentially Private Data Release for Data Mining				10.1145/2020408.2020487		2011