Optimal Semijoins for Distributed Database Systems
IEEE Transactions on Software Engineering
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
PERF join: an alternative to two-way semijoin and bloomjoin
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Summary cache: a scalable wide-area web cache sharing protocol
IEEE/ACM Transactions on Networking (TON)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
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
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
Executing SQL over encrypted data in the database-service-provider model
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Using unknowns to prevent discovery of association rules
ACM SIGMOD Record
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
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
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
Building decision tree classifier on private data
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
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Providing Database as a Service
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
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
Authenticating Query Results in Edge Computing
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Order preserving encryption for numeric data
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
When do data mining results violate privacy?
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Safely delegating data mining tasks
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
An Efficient Approximate Protocol for Privacy-Preserving Association Rule Mining
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
k-Support anonymity based on pseudo taxonomy for outsourcing of frequent itemset mining
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
CLAP: Collaborative pattern mining for distributed information systems
Decision Support Systems
Approximate privacy-preserving data mining on vertically partitioned data
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
Computer Methods and Programs in Biomedicine
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Privacy preserving association rule mining has been an active research area since recently. To this problem, there have been two different approaches--perturbation based and secure multiparty computation based. One drawback of the perturbation based approach is that it cannot always fully preserve individual's privacy while achieving precision of mining results. The secure multiparty computation based approach works only for distributed environment and needs sophisticated protocols, which constrains its practical usage. In this paper, we propose a new approach for preserving privacy in association rule mining. The main idea is to use keyed Bloom filters to represent transactions as well as data items. The proposed approach can fully preserve privacy while maintaining the precision of mining results. The tradeoff between mining precision and storage requirement is investigated. We also propose 驴-folding technique to further reduce the storage requirement without sacrificing mining precision and running time.