LOCATION BASED PRIVACY PRESERVING OUTSOURCED ASSOCIATION RULE MINING ON VERTICALLY PARTITIONED DATABASES
Anju Vijayan, Jasmine Jose · Journal of Emerging Technologies and Innovative Research · 2018
Mining the frequent item sets or association rules on a vertically partitioned databases in a secure manner is quite challenging. Identifying the frequent item set and association rules plays an important role in market basket analysis.Each data owners do not want to disclose their transaction details to other data owners.So by securing the data of each data owners helps to get their results securely without leaking the transaction details from a joint database. We propose another method for privacy preserving by identifying location of each data owner who put their data into a joint database.It helps to get the location of each data owners who wish to learn the frequent item sets or association rules and also adding an extra feature of viewing the number frequency of each items.