Top-Down Specialization for Information and Privacy Preservation
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Template-Based Privacy Preservation in Classification Problems
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Personalized privacy preservation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anonymizing sequential releases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Anatomy: simple and effective privacy preservation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Utility-based anonymization for privacy preservation with less information loss
ACM SIGKDD Explorations Newsletter
Handicapping attacker's confidence: an alternative to k-anonymization
Knowledge and Information Systems
Anonymizing Classification Data for Privacy Preservation
IEEE Transactions on Knowledge and Data Engineering
Minimality attack in privacy preserving data publishing
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
K-anonymization as spatial indexing: toward scalable and incremental anonymization
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Towards optimal k-anonymization
Data & Knowledge Engineering
An efficient hash-based algorithm for minimal k-anonymity
ACSC '08 Proceedings of the thirty-first Australasian conference on Computer science - Volume 74
Providing k-anonymity in data mining
The VLDB Journal — The International Journal on Very Large Data Bases
Workload-aware anonymization techniques for large-scale datasets
ACM Transactions on Database Systems (TODS)
Privacy Preserving Data Mining Research: Current Status and Key Issues
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
ARUBA: A Risk-Utility-Based Algorithm for Data Disclosure
SDM '08 Proceedings of the 5th VLDB workshop on Secure Data Management
Fixed-Parameter Tractability of Anonymizing Data by Suppressing Entries
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
Does enforcing anonymity mean decreasing data usefulness?
Proceedings of the 4th ACM workshop on Quality of protection
Towards privacy-preserving integration of distributed heterogeneous data
Proceedings of the 2nd PhD workshop on Information and knowledge management
Disclosure Analysis and Control in Statistical Databases
ESORICS '08 Proceedings of the 13th European Symposium on Research in Computer Security: Computer Security
A Novel Heuristic Algorithm for Privacy Preserving of Associative Classification
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
On the comparison of microdata disclosure control algorithms
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
An efficient online auditing approach to limit private data disclosure
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
HIDE: heterogeneous information DE-identification
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Anonymization-based attacks in privacy-preserving data publishing
ACM Transactions on Database Systems (TODS)
On the tradeoff between privacy and utility in data publishing
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Information Sciences: an International Journal
A multi-objective approach to data sharing with privacy constraints and preference based objectives
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
(α, k)-anonymous data publishing
Journal of Intelligent Information Systems
A distributed approach to enabling privacy-preserving model-based classifier training
Knowledge and Information Systems
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
An integrated framework for de-identifying unstructured medical data
Data & Knowledge Engineering
POkA: identifying pareto-optimal k-anonymous nodes in a domain hierarchy lattice
Proceedings of the 18th ACM conference on Information and knowledge management
Incremental privacy preservation for associative classification
Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
Transparent anonymization: Thwarting adversaries who know the algorithm
ACM Transactions on Database Systems (TODS)
The hardness and approximation algorithms for l-diversity
Proceedings of the 13th International Conference on Extending Database Technology
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
(α, k)-anonymity based privacy preservation by lossy join
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
Achieving k-anonymity via a density-based clustering method
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
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
Risk & distortion based K-anonymity
WISA'07 Proceedings of the 8th international conference on Information security applications
Privacy protection on multiple sensitive attributes
ICICS'07 Proceedings of the 9th international conference on Information and communications security
Allowing privacy protection algorithms to jump out of local optimums: an ordered greed framework
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
Privacy-preserving data mining through knowledge model sharing
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
Privacy-preserving data mining: A feature set partitioning approach
Information Sciences: an International Journal
Privacy-aware location data publishing
ACM Transactions on Database Systems (TODS)
Extending l-diversity to generalize sensitive data
Data & Knowledge Engineering
Relationships and data sanitization: a study in scarlet
Proceedings of the 2010 workshop on New security paradigms
Extended k-anonymity models against sensitive attribute disclosure
Computer Communications
Can the Utility of Anonymized Data be Used for Privacy Breaches?
ACM Transactions on Knowledge Discovery from Data (TKDD)
Publishing anonymous survey rating data
Data Mining and Knowledge Discovery
Priority-Based k-anonymity accomplished by weighted generalisation structures
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Achieving k-anonymity by clustering in attribute hierarchical structures
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Privacy streamliner: a two-stage approach to improving algorithm efficiency
Proceedings of the second ACM conference on Data and Application Security and Privacy
Limiting disclosure of sensitive data in sequential releases of databases
Information Sciences: an International Journal
Integrating private databases for data analysis
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Shadow: a middleware in pervasive computing environment for user controllable privacy protection
EuroSSC'06 Proceedings of the First European conference on Smart Sensing and Context
Disclosure analysis for two-way contingency tables
PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
On the identity anonymization of high-dimensional rating data
Concurrency and Computation: Practice & Experience
Information based data anonymization for classification utility
Data & Knowledge Engineering
A Knowledge Model Sharing Based Approach to Privacy-Preserving Data Mining
Transactions on Data Privacy
Anonymizing classification data using rough set theory
Knowledge-Based Systems
A general framework for privacy preserving data publishing
Knowledge-Based Systems
Journal of Computer Security
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The well-known privacy-preserved data mining modifies existing data mining techniques to randomized data. In this paper, we investigate data mining as a technique for masking data, therefore, termed data mining based privacy protection. This approach incorporates partially the requirement of a targeted data mining task into the process of masking data so that essential structure is preserved in the masked data. The idea is simple but novel: we explore the data generalization concept from data mining as a way to hide detailed information, rather than discover trends and patterns. Once the data is masked, standard data mining techniques can be applied without modification. Our work demonstrated another positive use of data mining technology: not only can it discover useful patterns, but also mask private information. We consider the following privacy problem: a data holder wants to release a version of datafor building classification models, but wants to protect against linking the released data to an external source for inferring sensitive information. We adapt an iterative bottom-up generalization from data mining to generalize the data. The generalized data remains useful to classification but becomes difficult to link to other sources. The generalization space is specified by a hierarchical structure of generalizations. A key is identifying the best generalization to climb up the hierarchy at each iteration. Enumerating all candidate generalizations is impractical. We present a scalable solution that examines at most one generalization in each iteration for each attribute involved in the linking.