Network data privacy security aggregation method based on big data pattern decomposition

被引:0
|
作者
Yu, Qiang [1 ]
机构
[1] Harbin Univ, Innovat & Entrepreneurship Coll, Harbin, Heilongjiang, Peoples R China
关键词
big data decomposition mode; network data privacy; secure aggregation; Paillier algorithm;
D O I
10.1504/IJCAT.2024.141357
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In order to improve the hiding rate of network data privacy information and shorten the encryption and decryption time, the paper proposes a new network data privacy security aggregation method based on big data pattern decomposition. Firstly, the empirical mode decomposition method is used to divide the upper and lower envelopes and complete the decomposition processing of network data. Secondly, the Paillier algorithm is used to calculate public and private keys and encrypt network data privacy. Finally, the encrypted ciphertext and signature are sent to the aggregator for secure aggregation of network data privacy through bilinear pairing. The experimental results show that the method proposed in this paper can improve the hiding rate of privacy information in network data, and the hiding rate of privacy information is basically above 95%, and the encryption and decryption time of network data privacy is significantly shortened.
引用
收藏
页码:26 / 33
页数:9
相关论文
共 50 条
  • [1] Aggregation Encryption Method of Social Network Privacy Data Based on Matrix Decomposition Algorithm
    Hongjing Bi
    Wireless Personal Communications, 2022, 127 : 369 - 383
  • [2] Aggregation Encryption Method of Social Network Privacy Data Based on Matrix Decomposition Algorithm
    Bi, Hongjing
    WIRELESS PERSONAL COMMUNICATIONS, 2022, 127 (01) : 369 - 383
  • [3] Big Data Security and Privacy
    Bertino, Elisa
    2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2016, : 3 - 3
  • [4] Big Data - Security and Privacy
    Bertino, Elisa
    2015 IEEE INTERNATIONAL CONGRESS ON BIG DATA - BIGDATA CONGRESS 2015, 2015, : 757 - 761
  • [5] Security and privacy in big data
    Xiang, Yang
    Au, Man Ho
    Kutylowsky, Miroslaw
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2016, 28 (10): : 2856 - 2857
  • [6] Special issue on Security, Privacy and Trust in network-based Big Data
    Wang, Hua
    Jiang, Xiaohong
    Kambourakis, Georgios
    INFORMATION SCIENCES, 2015, 318 : 48 - 50
  • [7] Security and Privacy Challenges in Big Data
    Wadhwa, Bhawna
    Tomar, Parul
    PROCEEDINGS OF THIRD DOCTORAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE, DOSCI 2022, 2023, 479 : 821 - 837
  • [8] Big Data security and privacy: A review
    Bardi, Matturdi
    Zhou Xianwei
    Li Shuai
    Lin Fuhong
    CHINA COMMUNICATIONS, 2014, 11 (02) : 135 - 145
  • [9] Big Data Security and Privacy Protection
    Zhang, Dongpo
    PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON MANAGEMENT AND COMPUTER SCIENCE (ICMCS 2018), 2018, 77 : 275 - 278
  • [10] Big data security and privacy protection
    Feng, Deng-Guo
    Zhang, Min
    Li, Hao
    Jisuanji Xuebao/Chinese Journal of Computers, 2014, 37 (01): : 246 - 258