Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
The key aspect of privacy protection is information sanitization intent for better data utility. The information is classified into three type’s, i.e., first identifiers which labels the identity, second quasi-identifiers the type of disclosure that needs to be focused on identity disclosure. A quasi-identifier refers to a attributes subsets that can uniquely identify tuples like personal health information consists name, address, gender, mobile number and third is sensitive attributes like disease, salary must be disclosed form others. Privacy is a key issue where prospects will be harmed by inappropriate disclosure of few assets.
How to cite this article:
G. Prabhakar Reddy, K. Sai Prasad, N. Chandra Shekar Reddy and R. Karthik. Privacy Preserving and Data Publishing using Tuple Grouping Algorithm.
DOI: https://doi.org/10.36478/jeasci.2018.930.933
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.930.933