Privacy Preserving Data Mining: Comparion of Three Groups and Four Groups Randomized Response Techniques

Abstract

Privacy and accuracy are the important issues in data mining when data is shared. A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Most of the methods use random permutation techniques to mask the data, for preserving the privacy of sensitive data. Randomized response techniques were developed for the purpose of protecting surveys privacy and avoiding biased answers. In randomized response techni que adds certain degree of randomness to the answer to prevent the biased data. The proposed work thesis is to enhance the privacy lev el 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 increases 65%.