PRIVACY PRESERVING DATA MINING IN FOUR GROUP RANDOMIZED RESPONSE TECHNIQUE USING ID3 AND CART ALGORITHM

Data mining is a process in which data collected from different sources is analyzed for useful information. Data mining is also known as knowledge discovery in database (KDD). Privacy and accuracy are the important issues in data mining when data is shared. Most of the methods use random permutation techniques to mask the data, for preserving the privacy of sensitive data. Randomize response techniques were developed for the purpose of protecting surveys privacy and avoiding biased answers. The proposed work thesis is to enhance the privacy level in RR technique using four group schemes. First according to the algorithm random attributes a, b, c, d were considered, Then the randomization have been performed on every dataset according to the values of theta. Then ID3 and CART algorithm are applied on the randomized data. The result shows that by increasing the group, the privacy level will increase. This work shows that as compared with three group scheme with four groups scheme the accuracy decreases 6 % but the privacy increase