C4.5: programs for machine learning
C4.5: programs for machine learning
Generalizing data to provide anonymity when disclosing information (abstract)
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Rough set approach to incomplete information systems
Information Sciences: an International Journal
Rules in incomplete information systems
Information Sciences: an International Journal
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Transforming data to satisfy privacy constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Top-Down Specialization for Information and Privacy Preservation
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anonymizing sequential releases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anatomy: simple and effective privacy preservation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Anonymizing Classification Data for Privacy Preservation
IEEE Transactions on Knowledge and Data Engineering
Data & Knowledge Engineering
k-Anonymization with Minimal Loss of Information
IEEE Transactions on Knowledge and Data Engineering
A framework for efficient data anonymization under privacy and accuracy constraints
ACM Transactions on Database Systems (TODS)
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Anonymizing healthcare data: a case study on the blood transfusion service
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Attacks on privacy and deFinetti's theorem
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Efficient Multidimensional Suppression for K-Anonymity
IEEE Transactions on Knowledge and Data Engineering
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Generating microdata with p-sensitive k-anonymity property
SDM'07 Proceedings of the 4th VLDB conference on Secure data management
Privacy-preserving data mining: A feature set partitioning approach
Information Sciences: an International Journal
Non-homogeneous generalization in privacy preserving data publishing
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Efficient Anonymizations with Enhanced Utility
Transactions on Data Privacy
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Differentially private data release for data mining
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Limiting disclosure of sensitive data in sequential releases of databases
Information Sciences: an International Journal
A practical approximation algorithm for optimal k-anonymity
Data Mining and Knowledge Discovery
k-Concealment: An Alternative Model of k-Type Anonymity
Transactions on Data Privacy
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The performance of classifiers and other data mining models can be significantly enhanced using the large repositories of digital data collected nowadays by public and private organizations. However, the original records stored in those repositories cannot be released to the data miners as they frequently contain sensitive information. The emerging field of Privacy Preserving Data Publishing (PPDP) deals with this important challenge. In this paper, we present NSVDist (Non-homogeneous generalization with Sensitive Value Distributions)-a new anonymization algorithm that, given minimal anonymity and diversity parameters along with an information loss measure, issues corresponding non-homogeneous anonymizations where the sensitive attribute is published as frequency distributions over the sensitive domain rather than in the usual form of exact sensitive values. In our experiments with eight datasets and four different classification algorithms, we show that classifiers induced from data generalized by NSVDist tend to be more accurate than classifiers induced using state-of-the-art anonymization algorithms.