Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
IEEE Transactions on Knowledge and Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Handicapping attacker's confidence: an alternative to k-anonymization
Knowledge and Information Systems
Privacy-preserving data mining in the malicious model
International Journal of Information and Computer Security
Privacy-preserving data publishing for cluster analysis
Data & Knowledge Engineering
International Journal of Computer Applications in Technology
A novel anonymization algorithm: Privacy protection and knowledge preservation
Expert Systems with Applications: An International Journal
Cluster analysis on time series gene expression data
International Journal of Business Intelligence and Data Mining
Preservation of Data Privacy Using PCA Based Transformation
ARTCOM '09 Proceedings of the 2009 International Conference on Advances in Recent Technologies in Communication and Computing
Privacy-Preserving Tuple Matching in Distributed Databases
IEEE Transactions on Knowledge and Data Engineering
A time-efficient pattern reduction algorithm for k-means clustering
Information Sciences: an International Journal
Collusion-Free Privacy Preserving Data Mining
International Journal of Intelligent Information Technologies
Classifying Consumer Comparison Opinions to Uncover Product Strengths and Weaknesses
International Journal of Intelligent Information Technologies
Combining Supervised Learning Techniques to Key-Phrase Extraction for Biomedical Full-Text
International Journal of Intelligent Information Technologies
Intelligent Information Retrieval Using Fuzzy Association Rule Classifier
International Journal of Intelligent Information Technologies
International Journal of Intelligent Information Technologies
An Ontology Based Model for Document Clustering
International Journal of Intelligent Information Technologies
Intelligent Decision Support System for Osteoporosis Prediction
International Journal of Intelligent Information Technologies
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Government agencies, business enterprises and non-profit organizations are searching for innovative methods to collect and analyze data about individuals or businesses to support their decision making processes. Data mining techniques are able to derive sensitive knowledge from unclassified data, causing a severe threat to privacy. The authors provide a promising solution to address the demand for privacy preservation in clustering analysis. They propose a novel dimensionality expansion based data privacy preservation technique using multi-layer artificial neural network. By applying this idea, the authors can project a low dimensional data into a high dimensional space to enhance the privacy level. Clustering was done using K-means and the results show that privacy level and the nature of data were very much preserved even after this transformation. The results arrived at were significant and the proposed method transformed the data better than the classical Geometric data transformation based methods.