Privacy preserving E-negotiation protocols based on secure multi-party computation

被引：2
|
作者：
Chakraborty, S [1 ]
Sehgal, SK [1 ]
Pal, AK [1 ]
机构：
[1] Indian Inst Management Calcutta, Kolkata, W Bengal, India
来源：
PROCEEDINGS OF THE IEEE SOUTHEASTCON 2004: EXCELLENCE IN ENGINEERING, SCIENCE, AND TECHNOLOGY | 2005年
关键词：
D O I：
10.1109/SECON.2005.1423287
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we have presented several algorithms based on distributed secure multiparty computation. We have applied these algorithms to develop e-negotiation protocols for collaborative supply chain planning. Preserving the privacy of the participants' data is an important issue in these protocols. The first protocol supports a policy of non-discriminatory pricing where the buying firms do not want to reveal their bids regarding price and demand before the supplier announces a fixed selling price common for all the buyers. Price is never disclosed for any buyer in this negotiation. In the second protocol we relax the assumption for the discrimination of prices for different buyer agents. The protocol attempts to find the joint gains between the buyers and seller by optimizing the total cost of the supply chain without disclosure of total cost or individual costs to each other or the mediator agent used for the purpose.
引用
收藏
页码：455 / 461
页数：7
相关论文
共 50 条
  • [1] Secure Multi-party Protocols for Privacy Preserving Data Mining
    Ma, Qingkai
    Deng, Ping
    [J]. WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, PROCEEDINGS, 2008, 5258 : 526 - 537
  • [2] Privacy preserving sequential pattern mining based on secure multi-party computation
    Ouyang, Weimin
    Huang, Qinhua
    [J]. 2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION ACQUISITION, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 2006, : 149 - 154
  • [3] Privacy preserving distributed data mining based on secure multi-party computation
    Liu, Jun
    Tian, Yuan
    Zhou, Yu
    Xiao, Yang
    Ansari, Nirwan
    [J]. COMPUTER COMMUNICATIONS, 2020, 153 : 208 - 216
  • [4] Secure Multi-Party Computation-Based Privacy-Preserving Authentication for Smart Cities
    Sucasas, Victor
    Aly, Abdelrahaman
    Mantas, Georgios
    Rodriguez, Jonathan
    Aaraj, Najwa
    [J]. IEEE TRANSACTIONS ON CLOUD COMPUTING, 2023, 11 (04) : 3555 - 3572
  • [5] Cross-system privacy preserving recommendation algorithm based on secure multi-party computation
    Zhang, Fuzhi
    Wang, Jingtao
    Chao, Jinbo
    [J]. Journal of Computational Information Systems, 2010, 6 (09): : 3013 - 3021
  • [6] Automatic Proofs of Privacy of Secure Multi-Party Computation Protocols Against Active Adversaries
    Pettai, Martin
    Laud, Peeter
    [J]. 2015 IEEE 28TH COMPUTER SECURITY FOUNDATIONS SYMPOSIUM CSF 2015, 2015, : 75 - 89
  • [7] Privacy-Preserving Secure Computation of Skyline Query in Distributed Multi-Party Databases †
    Qaosar, Mahboob
    Zaman, Asif
    Siddique, Md. Anisuzzaman
    Annisa
    Morimoto, Yasuhiko
    [J]. INFORMATION, 2019, 10 (03):
  • [8] Efficient privacy-preserving Gaussian process via secure multi-party computation
    Liu, Shiyu
    Luo, Jinglong
    Zhang, Yehong
    Wang, Hui
    Yu, Yue
    Xu, Zenglin
    [J]. JOURNAL OF SYSTEMS ARCHITECTURE, 2024, 151
  • [9] Preserving Privacy of Software-Defined Networking Policies by Secure Multi-Party Computation
    Zarezadeh, Maryam
    Mala, Hamid
    Khajeh, Homa
    [J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2020, 35 (04) : 863 - 874
  • [10] Preserving Privacy of Software-Defined Networking Policies by Secure Multi-Party Computation
    Maryam Zarezadeh
    Hamid Mala
    Homa Khajeh
    [J]. Journal of Computer Science and Technology, 2020, 35 : 863 - 874
12345