Pricing Personal Data Based on Information Entropy

被引：5
作者：
Shen, Yuncheng [1 ,2 ]
Guo, Bing [1 ]
Shen, Yan [3 ]
Duan, Xuliang [1 ]
Dong, Xiangqian [1 ]
Zhang, Hong [1 ]
机构：
[1] Sichuan Univ, Chengdu, Sichuan, Peoples R China
[2] Zhaotong Univ, Zhaotong, Peoples R China
[3] Chengdu Univ Informat Technol, Chengdu, Sichuan, Peoples R China
来源：
PROCEEDINGS OF THE 2019 2ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND INFORMATION MANAGEMENT (ICSIM 2019) / 2019 2ND INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (ICBDSC 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
personal data; arbitrage; data pricing; information entropy;
D O I：
10.1145/3305160.3305204
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Personal data is increasingly being traded online, for which data marketplace services have emerged to facilitate. Personal data is increasingly valuable to individuals and institutions. Be aware of the growing value of personal data, compensated use of personal data has become an inevitable trend. Therefore, how to reasonably price personal data becomes an urgent problem to be solved. We propose a novel personal data pricing method, which is based on information entropy and compute the price as the entropy of each data tuple. Our method can reasonably price personal data according to the value of the information entropy. This study shows that our model is arbitrage-freedom and can be adjusted dynamically.
引用
收藏
页码：143 / 146
页数：4
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