Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The inference problem: a survey
ACM SIGKDD Explorations Newsletter
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
An architecture for privacy-preserving mining of client information
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Assuring privacy when big brother is watching
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Privacy-preserving clustering with distributed EM mixture modeling
Knowledge and Information Systems
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
The Indiana Center for Database Systems at Purdue University
ACM SIGMOD Record
Template-Based Privacy Preservation in Classification Problems
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Towards low-perturbation anonymity preserving pattern discovery
Proceedings of the 2006 ACM symposium on Applied computing
Privacy-Preserving Computation of Bayesian Networks on Vertically Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Data Mining and Knowledge Discovery
Handicapping attacker's confidence: an alternative to k-anonymization
Knowledge and Information Systems
Safely delegating data mining tasks
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
Preserving privacy in association rule mining with bloom filters
Journal of Intelligent Information Systems
Extended RBAC-based design and implementation for a secure data warehouse
International Journal of Business Intelligence and Data Mining
Anonymity preserving pattern discovery
The VLDB Journal — The International Journal on Very Large Data Bases
Providing k-anonymity in data mining
The VLDB Journal — The International Journal on Very Large Data Bases
ACM SIGKDD Explorations Newsletter
Protecting business intelligence and customer privacy while outsourcing data mining tasks
Knowledge and Information Systems
Knowledge and Information Systems
Evaluating privacy threats in released database views by symmetric indistinguishability
Journal of Computer Security - Selected papers from the Third and Fourth Secure Data Management (SDM) workshops
Online pairing of VoIP conversations
The VLDB Journal — The International Journal on Very Large Data Bases
A distributed approach to enabling privacy-preserving model-based classifier training
Knowledge and Information Systems
A novel approach for privacy mining of generic basic association rules
Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
Publishing naive Bayesian classifiers: privacy without accuracy loss
Proceedings of the VLDB Endowment
Secure construction of k-unlinkable patient records from distributed providers
Artificial Intelligence in Medicine
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Privacy-preserving sequential pattern release
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Privacy-preserving data mining: A feature set partitioning approach
Information Sciences: an International Journal
Proceedings of the 9th annual ACM workshop on Privacy in the electronic society
Understanding privacy risk of publishing decision trees
DBSec'10 Proceedings of the 24th annual IFIP WG 11.3 working conference on Data and applications security and privacy
ACM Transactions on Database Systems (TODS)
Mixture of gaussian models and bayes error under differential privacy
Proceedings of the first ACM conference on Data and application security and privacy
k-Anonymous Decision Tree Induction
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Privacy-Preserving graph algorithms in the semi-honest model
ASIACRYPT'05 Proceedings of the 11th international conference on Theory and Application of Cryptology and Information Security
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Suppressing microdata to prevent probabilistic classification based inference
SDM'05 Proceedings of the Second VDLB international conference on Secure Data Management
Privacy-preserving distributed k-anonymity
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
Indistinguishability: the other aspect of privacy
SDM'06 Proceedings of the Third VLDB international conference on Secure Data Management
A Knowledge Model Sharing Based Approach to Privacy-Preserving Data Mining
Transactions on Data Privacy
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Privacy-preserving data mining has concentrated on obtaining valid results when the input data is private. An extreme example is Secure Multiparty Computation-based methods, where only the results are revealed. However, this still leaves a potential privacy breach: Do the results themselves violate privacy? This paper explores this issue, developing a framework under which this question can be addressed. Metrics are proposed, along with analysis that those metrics are consistent in the face of apparent problems.