Handicapping attacker's confidence: an alternative to k-anonymization
- 3 October 2006
- journal article
- Published by Springer Nature in Knowledge and Information Systems
- Vol. 11 (3) , 345-368
- https://doi.org/10.1007/s10115-006-0035-5
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- Top-Down Specialization for Information and Privacy PreservationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Data Privacy through Optimal k-AnonymizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- When do data mining results violate privacy?Published by Association for Computing Machinery (ACM) ,2004
- Tools for privacy preserving distributed data miningACM SIGKDD Explorations Newsletter, 2002
- The inference problemACM SIGKDD Explorations Newsletter, 2002
- Transforming data to satisfy privacy constraintsPublished by Association for Computing Machinery (ACM) ,2002
- Privacy preserving mining of association rulesPublished by Association for Computing Machinery (ACM) ,2002
- Using sample size to limit exposure to data miningJournal of Computer Security, 2000
- Mining association rules between sets of items in large databasesACM SIGMOD Record, 1993
- Suppression Methodology and Statistical Disclosure ControlJournal of the American Statistical Association, 1980