期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：10
页码：517-524
出版社：Science and Information Society (SAI)
摘要：In business association rules being considered as
important assets, play a vital role in its productivity and growth.
Different business partnership share association rules in order to
explore the capabilities to make effective decision for enhancement
of business and core capabilities. The fuzzy association
rule mining approach emerged out of the necessity to mine
quantitative data regularly present in database. An association
rule is sensitive when it violates few rules and regulation for
sharing particular nature of information to third world. Like
classical association rules, there is a need for some privacy
measures to be taken for retaining the standards and importance
of fuzzy association rules. Privacy preservation is used for valuable
information extraction and minimizing the risk of sensitive
information disclosure. Our proposed model mainly focuses to
secure the sensitive information revealing association rules. In
our model, sensitive fuzzy association rules are secured by
identifying sensitive fuzzy item to perturb fuzzified dataset. The
resulting transformed FARs are analyzed to conclude/calculate
the accuracy level of our model in context of newly generated
fuzzy association rules, hidden rules and lost rules. Extensive
experiments are carried out in order to demonstrate the results of
our proposed model. Privacy preservation of maximum number
of sensitive FARs by keeping minimum perturbation highlights
the significance of our model.
