Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Using sample size to limit exposure to data mining
Journal of Computer Security - Special issue on database security
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
Using unknowns to prevent discovery of association rules
ACM SIGMOD Record
Data Swapping: Balancing Privacy against Precision in Mining for Logic Rules
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Protecting Against Data Mining through Samples
Proceedings of the IFIP WG 11.3 Thirteenth International Conference on Database Security: Research Advances in Database and Information Systems Security
An Integrated Framework for Database Privacy Protection
Proceedings of the IFIP TC11/ WG11.3 Fourteenth Annual Working Conference on Database Security: Data and Application Security, Development and Directions
Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Hiding Association Rules by Using Confidence and Support
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Randomization in privacy preserving data mining
ACM SIGKDD Explorations Newsletter
Limiting privacy breaches in privacy preserving data mining
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A methodology for hiding knowledge in databases
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Privacy preserving frequent itemset mining
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Protecting Sensitive Knowledge By Data Sanitization
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
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
Using randomized response techniques for privacy-preserving data mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Knowledge and Data Engineering
State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Hiding Sensitive Patterns in Association Rules Mining
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Computational complexity of itemset frequency satisfiability
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Novel Method for Protecting Sensitive Knowledge in Association Rules Mining
COMPSAC '05 Proceedings of the 29th Annual International Computer Software and Applications Conference - Volume 01
A Framework for Evaluating Privacy Preserving Data Mining Algorithms*
Data Mining and Knowledge Discovery
IEEE Transactions on Knowledge and Data Engineering
A Border-Based Approach for Hiding Sensitive Frequent Itemsets
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Privacy Preserving Data Classification with Rotation Perturbation
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Suppressing Data Sets to Prevent Discovery of Association Rules
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Privacy Preserving ID3 Algorithm over Horizontally Partitioned Data
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
A reconstruction-based algorithm for classification rules hiding
ADC '06 Proceedings of the 17th Australasian Database Conference - Volume 49
Towards robustness in query auditing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Revisiting the uniqueness of simple demographics in the US population
Proceedings of the 5th ACM workshop on Privacy in electronic society
An integer programming approach for frequent itemset hiding
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
L-diversity: Privacy beyond k-anonymity
ACM Transactions on Knowledge Discovery from Data (TKDD)
Maximizing Accuracy of Shared Databases when Concealing Sensitive Patterns
Information Systems Research
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Two methods for privacy preserving data mining with malicious participants
Information Sciences: an International Journal
Privacy preserving clustering on horizontally partitioned data
Data & Knowledge Engineering
A new efficient privacy-preserving scalar product protocol
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Privacy-preserving classification of vertically partitioned data via random kernels
ACM Transactions on Knowledge Discovery from Data (TKDD)
Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Secure Multi-party Protocols for Privacy Preserving Data Mining
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Privacy-Preserving Computation and Verification of Aggregate Queries on Outsourced Databases
PETS '09 Proceedings of the 9th International Symposium on Privacy Enhancing Technologies
Communication-Efficient Privacy-Preserving Clustering
Transactions on Data Privacy
Privacy preserving clustering for multi-party
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
"You Might Also Like: " Privacy Risks of Collaborative Filtering
SP '11 Proceedings of the 2011 IEEE Symposium on Security and Privacy
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Hiding classification rules for data sharing with privacy preservation
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
ICDT'05 Proceedings of the 10th international conference on Database Theory
A further study on inverse frequent set mining
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Privacy-Preserving decision trees over vertically partitioned data
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
On private scalar product computation for privacy-preserving data mining
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
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At present, data mining algorithms are largely the domain of governments, large organisations and academia where they provide useful insight into the data. However, without the ability to assure privacy protection, the availability of datasets for research purposes may be impaired. Moreover, privacy-preservation is essential if data mining is to be permitted widespread use in government and commercial contexts. Indeed, as data mining algorithms become more widespread, even the datasets currently made available under limited release now may become more restricted. In addition, the ambiguous definitions currently in use hinder the assessment of the quality of the privacy preservation. This paper categorises the protection objectives during the data mining process into bands and then presents a reconceptualization of privacy-preserving data mining algorithms from the viewpoint of these bands. Existing algorithms from eight protection strategies are selected as examples to explain the six bands. Significantly, gaps are revealed in the Privacy Preserving Data Mining literature that indicate areas for future research.