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  • 标题:A Data Encryption and Approximate Recovery Strategy Based on Double Random Sorting and CGAN
  • 本地全文:下载
  • 作者:Dong Liu ; Haoda Wang ; Quanhong Liu
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:256
  • 页码:1-5
  • DOI:10.1051/e3sconf/202125602023
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The measurement data in the power system may be attacked and tampered during the transmission. For this problem, a data encryption and approximate recovery strategy based on double random sorting and CGAN is proposed. The double random sorting encryption algorithm is proposed based on the form of measurement data in plaintext. The randomness of pseudo-random number, random sequence and random sequence insertion will ensure the uncertainty of data block number, sorting order and insertion location of random sequence, which will definitely improve the security of measurement data. Besides, an approximate recovery strategy used to approximately recovery abnormal samples is proposed on the base of CGAN, which can ensure the accuracy of decryption. Finally, the feasibility, and effectiveness of the proposed method are analyzed on wind power and photovoltaic power historical dataset.
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