Association Rule Hiding Techniques for Privacy Preserving Data Mining: A Study

Association rule mining is an efficient data mining technique that recognizes the frequent items and associative rule based on a market basket data analysis for large set of transactional databases. The probability of most frequent data item occurrence of the transactional data items are calculated to present the associative rule that represents the habits of buying products of the customers in demand. Identifying associative rules of a transactional database in data mining may expose the confidentiality and privacy of an organization and individual. Privacy Preserving Data Mining (PPDM) is a solution for privacy threats in data mining. This issue is solved using Association Rule Hiding (ARH) techniques in Privacy Preserving Data Mining (PPDM). This research work on Association Rule Hiding technique in data mining performs the generation of sensitive association rules by the way of hiding based on the transactional data items. The property of hiding rules not the data makes the sensitive rule hiding process is a minimal side effects and higher data utility technique.

@article{P2015,
  title     = {Association Rule Hiding Techniques for Privacy Preserving Data Mining: A Study},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {6},
  number    = {12},
  year      = {2015},
  publisher = {The Science and Information Organization},
  author    = {Gayathiri P and Dr. B Poorna},
  doi       = {10.14569/IJACSA.2015.061232},
  url       = {https://doi.org/10.14569/IJACSA.2015.061232}
}