Privacy-friendly Blockchain based Data Trading and Tracking

被引：2
|
作者：
Wu, Zhenan [1 ]
Zheng, Han [1 ]
Zhang, Lan [1 ]
Li, Xiang-Yang [1 ]
机构：
[1] Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei, Peoples R China
来源：
5TH INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING AND COMMUNICATIONS (BIGCOM 2019) | 2019年
基金：
国家重点研发计划;
关键词：
D O I：
10.1109/BIGCOM.2019.00040
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Data trading has become a promising way to bridge numerous data islands and benefit a wide range of data driven applications. However, due to the high risk of data privacy, the easy-to-copy feature of data, and potential malicious behaviors of users, there still lacks data trading solutions to provide privacy protection, copyright/ownership protection and auditability of user behaviors. In this work, we propose a blockchain and smart contract based framework to keep tamper-proof records of data trading transactions, which also preserves users' identity, behavior and data privacy. Data fingerprint is introduced to track data and protect data ownership. A set of protocols are also designed to prevent dishonest behaviors and ensure the security of data trading.
引用
收藏
页码：240 / 244
页数：5
相关论文
共 50 条
  • [21] Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking
    Pavlidis, Nikolaos
    Sendros, Andreas
    Tsiolakis, Theodoros
    Kostamis, Periklis
    Karasoulas, Christos
    Briola, Eleni
    Nikolaidis, Christos Chrysanthos
    Perifanis, Vasilis
    Drosatos, George
    Katsiri, Eleftheria
    Filippidou, Despoina Elisavet
    Manos, Anastasios
    Efraimidis, Pavlos S.
    JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2025, 14 (01)
  • [22] BioID: A Privacy-Friendly Identity Document
    Balli, Fatih
    Durak, F. Betul
    Vaudenay, Serge
    SECURITY AND TRUST MANAGEMENT, STM 2019, 2019, 11738 : 53 - 70
  • [23] Outlining "Data track": Privacy-friendly data maintenance for end-users
    Pettersson, John Soren
    Fischer-Hubner, Simone
    Bergmann, Mike
    ADVANCES IN INFORMATION SYSTEMS DEVELOPMENT, VOL 2: NEW METHODS AND PRACTICE FOR THE NETWORKED SOCIETY, 2007, : 215 - +
  • [24] Attribute-Based Privacy-Friendly Access Control with Context
    Put, Andreas
    De Decker, Bart
    E-BUSINESS AND TELECOMMUNICATIONS (ICETE 2016), 2017, 764 : 291 - 315
  • [25] Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors
    Damer, Naser
    Lopez, Cesar Augusto Fontanillo
    Fang, Meiling
    Spiller, Noemie
    Pham, Minh Vu
    Boutros, Fadi
    2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2022, 2022, : 1605 - 1616
  • [26] SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data
    Boutros, Fadi
    Huber, Marco
    Siebke, Patrick
    Rieber, Tim
    Damer, Naser
    2022 IEEE INTERNATIONAL JOINT CONFERENCE ON BIOMETRICS (IJCB), 2022,
  • [27] Homomorphic Encryption for Privacy-Friendly Augmented Democracy
    Brabant, Matthieu
    Pereira, Olivier
    Meaux, Pierrick
    2022 IEEE 21ST MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (IEEE MELECON 2022), 2022, : 18 - 23
  • [28] Learning Whom to Trust in a Privacy-Friendly Way
    Ries, Sebastian
    Fischlin, Marc
    Martucci, Leonardo A.
    Muhlhauser, Max
    TRUSTCOM 2011: 2011 INTERNATIONAL JOINT CONFERENCE OF IEEE TRUSTCOM-11/IEEE ICESS-11/FCST-11, 2011, : 214 - 225
  • [29] Privacy-Friendly Sharing of Health Data Using a Reference Architecture for Health Data Spaces
    Ahmadian, Amir Shayan
    Franke, Sebastian
    Gnoguem, Charly N.
    Jurjens, Jan
    PROCEEDINGS OF 4TH ECLIPSE SECURITY, AI, ARCHITECTURE AND MODELLING CONFERENCE ON DATA SPACES, ESAAM 2024, 2024, : 103 - 112
  • [30] Understanding Privacy-friendly Design of Robot Eyes
    Shinohara, Maino
    Sakamoto, Daisuke
    Young, James E.
    Ono, Tetsuo
    PROCEEDINGS OF THE 11TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2023, 2023, : 133 - 141
12345