A modified random perturbation method for database security
ACM Transactions on Database Systems (TODS)
Bias avoidance and measures of confidentiality for the noise addition method of database disclosure control
The use of added error to avoid disclosure in microdata releases
The use of added error to avoid disclosure in microdata releases
Model Based Disclosure Protection
Inference Control in Statistical Databases, From Theory to Practice
Re-identifying register data by survey data using cluster analysis: an empirical study
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Information Sciences—Informatics and Computer Science: An International Journal
Spatial and non-spatial model-based protection procedures for the release of business microdata
Statistics and Computing
Maximum entropy simulation for microdata protection
Statistics and Computing
Random-data perturbation techniques and privacy-preserving data mining
Knowledge and Information Systems
Achieving Privacy in Trust Negotiations with an Ontology-Based Approach
IEEE Transactions on Dependable and Secure Computing
Efficient multivariate data-oriented microaggregation
The VLDB Journal — The International Journal on Very Large Data Bases
A polynomial-time approximation to optimal multivariate microaggregation
Computers & Mathematics with Applications
Micro-SOM: A Linear-Time Multivariate Microaggregation Algorithm Based on Self-Organizing Maps
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Privacy Preserving Categorical Data Analysis with Unknown Distortion Parameters
Transactions on Data Privacy
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Privacy-aware regression modeling of participatory sensing data
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Measurement error and statistical disclosure control
PSD'10 Proceedings of the 2010 international conference on Privacy in statistical databases
Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
Edit constraints on microaggregation and additive noise
PSDML'10 Proceedings of the international ECML/PKDD conference on Privacy and security issues in data mining and machine learning
On the declassification of confidential documents
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
Combinations of SDC methods for microdata protection
PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Information fusion in data privacy: A survey
Information Fusion
Kd-trees and the real disclosure risks of large statistical databases
Information Fusion
Preventing automatic user profiling in Web 2.0 applications
Knowledge-Based Systems
Achieving comparability of earnings
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
Heuristic supervised approach for record linkage
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
Cloud-enabled privacy-preserving collaborative learning for mobile sensing
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Effective sanitization approaches to hide sensitive utility and frequent itemsets
Intelligent Data Analysis
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Microdata protection by adding noise is being discussed for more than 20 years now. Several algorithms were developed that have different characteristics. The simplest algorithm consists of adding white noise to the data. More sophisticated methods use more or less complex transformations of the data and more complex error-matrices to improve the results. This contribution gives an overview over the different algorithms and discusses their properties in terms of analytical validity and level of protection. Therefore some theoretical considerations are shown and an illustrating empirical example is given.