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

Authors: Qiang Yu

Addresses: Innovation and Entrepreneurship College, Harbin University, Harbin, Heilongjiang Province, China

Abstract: 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.

Keywords: big data decomposition mode; network data privacy; secure aggregation; Paillier algorithm.

DOI: 10.1504/IJCAT.2024.141357

International Journal of Computer Applications in Technology, 2024 Vol.74 No.1/2, pp.26 - 33

Received: 30 Oct 2023
Accepted: 13 Feb 2024
Published online: 09 Sep 2024 *

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