Security in Computing
Datafly: A System for Providing Anonymity in Medical Data
Proceedings of the IFIP TC11 WG11.3 Eleventh International Conference on Database Securty XI: Status and Prospects
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Transforming data to satisfy privacy constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The role of cryptography in database security
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Bottom-Up Generalization: A Data Mining Solution to Privacy Protection
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Top-Down Specialization for Information and Privacy Preservation
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Privacy and Ownership Preserving of Outsourced Medical Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Injecting utility into anonymized datasets
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Utility-based anonymization using local recoding
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalization in privacy-aware highly dynamic systems
Communications of the ACM - Privacy and security in highly dynamic systems
Communications of the ACM - Privacy and security in highly dynamic systems
Capturing data usefulness and privacy protection in K-anonymisation
Proceedings of the 2007 ACM symposium on Applied computing
What Anyone Can Know: The Privacy Risks of Social Networking Sites
IEEE Security and Privacy
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Tuning anonymity level for assuring high data quality: an empirical study.
ESEM '07 Proceedings of the First International Symposium on Empirical Software Engineering and Measurement
Fast data anonymization with low information loss
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Data utility and privacy protection trade-off in k-anonymisation
PAIS '08 Proceedings of the 2008 international workshop on Privacy and anonymity in information society
A tree-based approach to preserve the privacy of software engineering data and predictive models
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
| Hi-index | 0.00 |
Preserving data privacy is becoming an urgent issue to cope with. Among different technologies, anonymization techniques offer many advantages, even if preliminary investigations suggest that they could deteriorate the usefulness of data. We carried out an empirical study in order to understand to which extent it is possible to enforce anonymization, and thus protect sensitive information, without degrading usefulness of data under unacceptable thresholds. Moreover, we analyzed also if re-writing queries could help reduce drawbacks of anonymization.