%0 Journal Article %1 sharma2013enhancing %A Sharma, Rahul %D 2013 %E Sharma, Anand %J International Journal on Recent and Innovation Trends in Computing and Communication %K CART Data Four Groups ID3 Issue Mining Multi PPDM, Privacy %N 12 %P 5 %T Enhancing Privacy for Multi Group Data Sets in PPDM Using ID3 and CART Algorithm %U http://ijritcc.org/IJRITCC%20Vol_1%20Issue_12/Enhancing%20Privacy%20for%20Multi%20Group%20Data%20Sets%20in%20PPDM%20Using%20ID3%20and%20CART%20Algorithm.pdf %V 1 %X Data mining is a process in which data collected from different sources is analyzed for useful information. Because data mining tools provides a base for upcoming trends and reactions by reading through databases for secret patterns, they allow organizations to make proactive, knowledge-driven actions and the problems that were previously too much time-consuming to resolve. Data mining software is one of a number of analytical tools for analyzing data. In the field of data mining the Privacy is most important issue when data is shared. A fruitful direction for future trends of data mining research will be the enhancement of methods that incorporate privacy concerns. 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 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 increases 65%.

@article{sharma2013enhancing, abstract = {Data mining is a process in which data collected from different sources is analyzed for useful information. Because data mining tools provides a base for upcoming trends and reactions by reading through databases for secret patterns, they allow organizations to make proactive, knowledge-driven actions and the problems that were previously too much time-consuming to resolve. Data mining software is one of a number of analytical tools for analyzing data. In the field of data mining the Privacy is most important issue when data is shared. A fruitful direction for future trends of data mining research will be the enhancement of methods that incorporate privacy concerns. 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 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 increases 65%.}, added-at = {2014-01-14T18:03:48.000+0100}, author = {Sharma, Rahul}, biburl = {https://www.bibsonomy.org/bibtex/2c988087ec91280248c7f52e465540606/ijritcc}, editor = {Sharma, Anand}, interhash = {675fcfae7e17940e9de6c196913e798a}, intrahash = {c988087ec91280248c7f52e465540606}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {CART Data Four Groups ID3 Issue Mining Multi PPDM, Privacy}, month = {December}, number = 12, pages = 5, timestamp = {2014-01-14T18:03:48.000+0100}, title = {Enhancing Privacy for Multi Group Data Sets in PPDM Using ID3 and CART Algorithm}, url = {http://ijritcc.org/IJRITCC%20Vol_1%20Issue_12/Enhancing%20Privacy%20for%20Multi%20Group%20Data%20Sets%20in%20PPDM%20Using%20ID3%20and%20CART%20Algorithm.pdf}, volume = 1, year = 2013 }