STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Introduction to algorithms
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Secure multi-party computation problems and their applications: a review and open problems
Proceedings of the 2001 workshop on New security paradigms
Modern Information Retrieval
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Using unknowns to prevent discovery of association rules
ACM SIGMOD Record
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Hiding Association Rules by Using Confidence and Support
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Cryptographic techniques for privacy-preserving data mining
ACM SIGKDD Explorations Newsletter
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Disclosure Limitation of Sensitive Rules
KDEX '99 Proceedings of the 1999 Workshop on Knowledge and Data Engineering Exchange
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
IEEE Transactions on Knowledge and Data Engineering
Optimal randomization for privacy preserving data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A new scheme on privacy preserving association rule mining
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Data transformation for privacy-preserving data mining
Data transformation for privacy-preserving data mining
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A MaxMin approach for hiding frequent itemsets
Data & Knowledge Engineering
Hiding Frequent Patterns under Multiple Sensitive Thresholds
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
Hiding Predictive Association Rules on Horizontally Distributed Data
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Hiding collaborative recommendation association rules on horizontally partitioned data
Intelligent Data Analysis
K-anonymous association rule hiding
ASIACCS '10 Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security
k-anonymization without Q-S associations
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
A new parallel association rule mining algorithm on distributed shared memory system
International Journal of Business Intelligence and Data Mining
Effective sanitization approaches to hide sensitive utility and frequent itemsets
Intelligent Data Analysis
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The sharing of association rules has been proven beneficial in business collaboration, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal strategic patterns called sensitive rules. The challenge here is how to protect the sensitive rules without losing the benefit of mining. To address this problem, we propose a unified framework that combines: a set of algorithms to protect sensitive knowledge; retrieval facilities to speed up the process of knowledge protecting; and a set of metrics to evaluate the effectiveness of the proposed algorithms in terms of information loss and private information disclosure.