Privacy Preserving Association Rule Mining in Horizontally Partitioned Databases Without Involving Trusted Third Party (TTP)

被引：4
|
作者：
Modi, Chirag N. [1 ]
Patil, Ashwini R. [2 ]
机构：
[1] Natl Inst Technol Goa, Farmagudi, Goa, India
[2] Natl Inst Technol, Surat, India
来源：
PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING, NETWORKING AND INFORMATICS, ICACNI 2015, VOL 2 | 2016年 / 44卷
关键词：
Distributed association rule; Privacy; Elliptic curve cryptography;
D O I：
10.1007/978-81-322-2529-4_57
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this research work, we design a security protocol that derives association rules securely from the horizontally distributed databases without a trusted third party (TTP), even communication channel is unsecured between involving sites. It ensures privacy and security of owner's with the help of elliptic curve based Diffie-Hellman and Digital Signature Algorithm.
引用
收藏
页码：549 / 555
页数：7
相关论文
共 50 条
  • [1] Privacy-Preserving-Outsourced Association Rule Mining on Vertically Partitioned Databases
    Li, Lichun
    Lu, Rongxing
    Choo, Kim-Kwang Raymond
    Datta, Anwitaman
    Shao, Jun
    [J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2016, 11 (08) : 1847 - 1861
  • [2] An Improved EMHS Algorithm for Privacy Preserving in Association Rule Mining on Horizontally Partitioned Database
    Adhvaryu, Rachit
    Domadiya, Nikunj
    [J]. SECURITY IN COMPUTING AND COMMUNICATIONS, 2014, 467 : 272 - 280
  • [3] Brief Announcement: Privacy Preserving Mining of Distributed Data Using a Trusted and Partitioned Third Party
    Maoz, Nir
    Gudes, Ehud
    [J]. CYBER SECURITY CRYPTOGRAPHY AND MACHINE LEARNING (CSCML 2017), 2017, 10332 : 193 - 195
  • [4] Privacy-Preserving Two-Party Distributed Association Rules Mining on Horizontally Partitioned Data
    Zhang, Feng
    Rong, Chunming
    Zhao, Gansen
    Wu, Jinxia
    Wu, Xiangning
    [J]. 2013 INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA (CLOUDCOM-ASIA), 2013, : 633 - 640
  • [5] Privacy-preserving distributed mining of association rules on horizontally partitioned data
    Kantarcioglu, M
    Clifton, C
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2004, 16 (09) : 1026 - 1037
  • [6] Privacy-Preserving Data Analysis without Trusted Third Party
    Miyaji, Atsuko
    Takahashi, Tomoka
    Wang, Ping-Lun
    Yamatsuki, Tatsuhiro
    Mimoto, Tomoaki
    [J]. 2022 IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS, TRUSTCOM, 2022, : 710 - 717
  • [7] Privacy Preserving Probabilistic Record Linkage Without Trusted Third Party
    Lazrig, Ibrahim
    Ong, Toan C.
    Ray, Indrajit
    Ray, Indrakshi
    Jiang, Xiaoqian
    Vaidya, Jaideep
    [J]. 2018 16TH ANNUAL CONFERENCE ON PRIVACY, SECURITY AND TRUST (PST), 2018, : 75 - 84
  • [8] Privacy-preserving association rule mining for horizontally partitioned healthcare data: a case study on the heart diseases
    Domadiya, Nikunj
    Rao, Udai Pratap
    [J]. SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2018, 43 (08):
  • [9] ElGamal Homomorphic Encryption-Based Privacy Preserving Association Rule Mining on Horizontally Partitioned Healthcare Data
    Domadiya N.
    Rao U.P.
    [J]. Journal of The Institution of Engineers (India): Series B, 2022, 103 (03) : 817 - 830
  • [10] Privacy-preserving association rule mining for horizontally partitioned healthcare data: a case study on the heart diseases
    Nikunj Domadiya
    Udai Pratap Rao
    [J]. Sādhanā, 2018, 43
12345