Personal big data pricing method based on differential privacy

被引：15
|
作者：
Shen, Yuncheng [1 ,2 ]
Guo, Bing [1 ]
Shen, Yan [3 ]
Duan, Xuliang [1 ]
Dong, Xiangqian [1 ]
Zhang, Hong [1 ]
Zhang, Chuanwu [4 ]
Jiang, Yuming [1 ]
机构：
[1] Sichuan Univ, Coll Comp Sci, Chengdu 610065, Peoples R China
[2] Zhaotong Univ, Coll Informat Sci & Technol, Zhaotong 657000, Peoples R China
[3] Chengdu Univ Informat Technol, Sch Comp Sci, Chengdu 610054, Peoples R China
[4] Southwest Minzu Univ, Coll Elect & Informat Engn, Chengdu 610041, Peoples R China
来源：
COMPUTERS & SECURITY | 2022年 / 113卷
基金：
中国国家自然科学基金;
关键词：
Personal big data; Data privacy; Privacy protection; Differential privacy; Positive pricing; Reverse pricing; Privacy budget; Privacy compensation; VIEWS;
D O I：
10.1016/j.cose.2021.102529
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 big data can greatly promote social management, business applications, and personal services, and bring certain economic benefits to users. The difficulty with personal big data security and privacy protection lies in realizing the maximization of the value of personal big data and in striking a balance between data privacy protection and sharing on the premise of satisfying personal big data security and privacy protection. Thus, in this paper, we propose a personal big data p ricing m ethod based on d ifferential p rivacy (PMDP). We design two different mechanisms of positive and reverse pricing to reasonbly price personal big data. We perform aggregate statistics on an open dataset and extensively evaluated its performance. The experimental results show that PMDP can provide reasonable pricing for personal big data and fair compensation to data owners, ensuring an arbitrage-free condition and finding a balance between privacy protection and data utility. (c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数：18
相关论文
共 50 条
  • [41] Technical and Legal Strategic Approaches Protecting the Privacy of Personal Data in Cloud-Based Big Data Applications
    Arikan, Suleyman Muhammed
    [J]. 2022 10TH INTERNATIONAL SYMPOSIUM ON DIGITAL FORENSICS AND SECURITY (ISDFS), 2022,
  • [42] Privacy Cost Analysis and Privacy Protection Based on Big Data
    周蔷
    岳开旭
    段垚
    [J]. Journal of Donghua University(English Edition), 2019, 36 (01) : 96 - 105
  • [43] Big Data Management System for Personal Privacy Using SW and SDF
    Sarjapur, Kashinath
    Suma, V.
    Christa, Sharon
    Rao, Jawahar
    [J]. INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016, 2016, 434 : 757 - 763
  • [44] Research on the Protection of Personal Privacy of Tourism Consumers in the Era of Big Data
    Wang, Chunyan
    [J]. 2018 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2018), 2018, : 428 - 431
  • [45] Harnessing Big Personal Data, with Scrutable User Modelling for Privacy and Control
    Kay, Judy
    [J]. MM'15: PROCEEDINGS OF THE 2015 ACM MULTIMEDIA CONFERENCE, 2015, : 1 - 2
  • [46] Privacy A Big Issue As Major Automakers Sell Consumers' Personal Data
    李念晨
    [J]. 语数外学习(高中版上旬), 2023, (11) : 94 - 94
  • [47] A Novel Method Of Privacy-preserving based on Compressive Sensing for Big Data
    Lyu, Denglong
    Zhu, Shibing
    [J]. PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC), 2017, : 593 - 601
  • [48] Deep Learning: Differential Privacy Preservation in the Era of Big Data
    Vasa, Jalpesh
    Thakkar, Amit
    [J]. JOURNAL OF COMPUTER INFORMATION SYSTEMS, 2023, 63 (03) : 608 - 631
  • [49] Differential Privacy and Distributed Online Learning for Wireless Big Data
    Li, Chencheng
    Zhou, Pan
    Jiang, Tao
    [J]. 2015 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS & SIGNAL PROCESSING (WCSP), 2015,
  • [50] Differential Privacy Preserving in Big Data Analytics for Connected Health
    Chi Lin
    Zihao Song
    Houbing Song
    Yanhong Zhou
    Yi Wang
    Guowei Wu
    [J]. Journal of Medical Systems, 2016, 40
12345