PDF | Classification of data with privacy preservation is a fundamental problem in privacy preserving data mining. The privacy goal requires. Classification is a fundamental problem in data analysis. Training a classifier requires accessing a large collection of data. Releasing. Classification of data with privacy preservation is a fundamental One way to achieve both is to anonymize the dataset that contains the.
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Anonymizing Classification Data for Privacy Preservation – Semantic Scholar
Skip to search form Skip to main content. Fung and Ke Wang and Philip S. FungKe WangPhilip S. Classification is a fundamental problem in data analysis.
Anonymizing classification data for privacy preservation
Training a classifier requires accessing a large collection of data. Releasing person-specific data, such as customer data or patient records, may pose a threat to an individual’s privacy. This paper has highly influenced 20 other papers. This paper has citations.
From This Paper Topics from this paper. Topics Discussed in This Paper. Data anonymization Privacy Distortion.
Real life Statistical classification Requirement. Citations Publications citing this paper. Showing of extracted citations. Enhanced anonymization algorithm to preserve confidentiality of data in public cloud Amalraj IrudayasamyArockiam Lawrence International Conference on Information Society…. Citation Statistics Citations 0 20 40 ’09 ’12 pdeservation ‘ Semantic Scholar estimates that this publication has citations based on the available data.
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Transforming data to satisfy privacy constraints Vijay S. Anonymizing Classification Data for Privacy Preservation.