A Practical Three-dimensional Privacy-preserving Approximate Convex Hulls Protocol

被引:1
|
作者
Li, Dong [1 ]
Huang, Liusheng [1 ]
Yang, Wei [1 ]
Zhu, Youwen [1 ]
Luo, Yonglong [1 ]
Chen, Zhili [1 ]
Li, Lingjun [1 ]
Ye, Yuri [1 ]
机构
[1] Univ Sci & Technol China, Natl High Performance Comp Ctr Hefei, Dept Comp Sci & Technol, Hefei 230027, Peoples R China
关键词
D O I
10.1109/FCST.2008.11
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Convex Hulls Problem is a special case of Privacy-preserving Geometry Problem in the inquiry of Secure Multi-Party Computation. In the past, only in two-dimensional space privacy-preserving convex hulls have been investigated, and there is little focus in the three-dimensional space. However three-dimensional privacy-preserving convex hulls can be applied in many fields, such as researching and exploration of the space, military, corporately finding the union range based on sensitive data from two parties. Approximate convex hulls have more advantages than conventional convex hulls in the theme of Secure Multi-Party Computation because it can hide the private points on the vertices. In this paper we first present a practical privacy-preserving protocol to solve the three dimensional approximate convex hulls problem; we also discuss the correctness, security, and performance of our protocol.
引用
收藏
页码:17 / 23
页数:7
相关论文
共 50 条
  • [21] FTP: An Approximate Fast Privacy-Preserving Equality Test Protocol for Authentication in Internet of Things
    Zhu, Youwen
    Zhang, Yue
    Yuan, Jiabin
    Wang, Xianmin
    SECURITY AND COMMUNICATION NETWORKS, 2018,
  • [22] A Practical System for Privacy-Preserving Collaborative Filtering
    Chow, Richard
    Pathak, Manas A.
    Wang, Cong
    12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), 2012, : 547 - 554
  • [23] A Practical Privacy-Preserving Algorithm for Document Data
    Mimoto, Tomoaki
    Kiyomoto, Shinsaku
    Kitamura, Koji
    Miyaji, Atsuko
    2020 IEEE 19TH INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (TRUSTCOM 2020), 2020, : 1377 - 1384
  • [24] Toward practical privacy-preserving linear regression
    Xu, Wenju
    Wang, Baocang
    Liu, Jiasen
    Chen, Yange
    Duan, Pu
    Hong, Zhiyong
    INFORMATION SCIENCES, 2022, 596 (119-136) : 119 - 136
  • [25] Practical Verifiable & Privacy-Preserving Double Auctions
    Zahedani, Armin Memar
    Vos, Jelle
    Erkin, Zekeriya
    18TH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY & SECURITY, ARES 2023, 2023,
  • [26] Practical Privacy-Preserving Protocols for Criminal Investigations
    Kerschbaum, Florian
    Schaad, Andreas
    Biswas, Debmalya
    ISI: 2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENCE AND SECURITY INFORMATICS, 2009, : 197 - 199
  • [27] A Practical Framework for Privacy-Preserving Data Analytics
    Fan, Liyue
    Jin, Hongxia
    PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW 2015), 2015, : 311 - 321
  • [28] A Practical System for Privacy-Preserving Video Surveillance
    Bentafat, Elmahdi
    Rathore, M. Mazhar
    Bakiras, Spiridon
    APPLIED CRYPTOGRAPHY AND NETWORK SECURITY (ACNS 2020), PT II, 2020, 12147 : 21 - 39
  • [29] A Practical Framework for Privacy-Preserving NoSQL Databases
    Macedo, Ricardo
    Paulo, Joao
    Pontes, Rogerio
    Portela, Bernardo
    Oliveira, Tiago
    Matos, Miguel
    Oliveira, Rui
    2017 IEEE 36TH INTERNATIONAL SYMPOSIUM ON RELIABLE DISTRIBUTED SYSTEMS (SRDS), 2017, : 11 - 20
  • [30] Fast computation of three-dimensional convex hulls using graphics hardware
    Osami Yamamoto
    Japan Journal of Industrial and Applied Mathematics, 2005, 22 : 291 - 310