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An anonymization technique using intersected decision trees
Samuel Fletcher,
Md Zahidul Islam
Data Science and Engineering Research Unit
DaMRG - Data Mining Research Group
Machine Vision and Digital Health (MaViDH) Research Group
Cyber Security Research Group (CSRG)
Imaging and Sensing Research Group
Health Services Research Group
Computing, Mathematics and Engineering
Research output
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Contribution to journal
›
Article
›
peer-review
9
Citations (Scopus)
59
Downloads (Pure)
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Keyphrases
Data Mining Techniques
100%
Decision Tree
100%
Evaluation Criteria
100%
Evaluation Method
100%
Privacy Preserving Data Mining
100%
Anonymization Algorithm
100%
Prediction Accuracy
50%
Lack of Trust
50%
Organizational Trust
50%
Noise Addition
50%
Individual Privacy
50%
Decision Forest
50%
Logic Rules
50%
Security Evaluation
50%
Adding Noise
50%
Data Quality Assessment
50%
Computer Science
Data Mining Technique
100%
Anonymization
100%
Data Mining
100%
Decision Trees
100%
privacy preserving data mining
100%
Evaluation Criterion
100%
Quality Evaluation
50%
Individual Privacy
50%
Noise Addition
50%
Massive Amount
50%
Security Evaluation
50%
Prediction Accuracy
50%
Experimental Result
50%
Collected Data
50%