Secured segmentation for ICD datasets

Data publishing can infringe individual privacy. When there is a necessity to extract knowledge from data mining results, there should be a discipline followed by not disclosing individual information. There is an opportunity for the user to interpret specific individual information from data mining results and further misuse the interpreted results, resulting in infringement of privacy. Privacy preserving data publishing research attempts to guarantee accurate results yet preserves privacy of individual information. The proposed Secured Segmentation technique guarantees better accuracy (41.5) and privacy when dealing with record linkage and attribute linkage attacks. Secured Segmentation technique demonstrates K-anonymity to retain privacy when dealing with record linkage attacks. It also demonstrates L-diversity and t-closeness to retain privacy when dealing with attribute linkage attacks.

Automated summary

Data publishing can infringe individual privacy, but privacy preserving data publishing research aims to ensure accurate results while protecting privacy. The Secured Segmentation technique provides better accuracy and privacy when dealing with attacks.