Affiliations: [a] School of Mathematics and Information Technology, Jiangsu Second Normal University, Nanjing, 210013, China | [b] School of Computing, Nanjing University of Science and Technology ZIJIN College, Nanjing, 210000, China
Abstract: Aiming at the problems of low mining accuracy and high privacy protection data noise in privacy protection data mining methods in blockchain, a privacy protection data mining algorithm in blockchain based on decision tree classification is proposed. Extract the privacy protection data in the blockchain, calculate and update the distance between the data in the data set to be denoised, and denoise the updated data. Finally, starting from the root of the decision tree, calculate the information gain value of this part of privacy protection data, determine the attribute probability of privacy protection data, and complete the in-depth mining of privacy protection data in the blockchain through the calculation of decision leaf density value. The experimental results show that the mining accuracy of the proposed algorithm is always more than 90%, and the data noise is stable below 0.6 dB.
Keywords: Decision tree classification, blockchain, privacy protection data, attribute probability
