Privacy protection data mining algorithm in blockchain based on decision tree classification

被引：1
|
作者：
Cao, Yu [1 ]
Wei, Wei [2 ]
Zhou, Jin [1 ]
机构：
[1] Jiangsu Second Normal Univ, Sch Math & Informat Technol, Nanjing 210013, Peoples R China
[2] Nanjing Univ Sci & Technol ZIJIN Coll, Sch Comp, Nanjing 210000, Peoples R China
来源：
WEB INTELLIGENCE | 2022年 / 20卷 / 02期
关键词：
Decision tree classification; blockchain; privacy protection data; attribute probability; SYSTEMS;
D O I：
10.3233/WEB-210485
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：103 / 112
页数：10
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