1 publication

• Published Subscription 17 Mar 2023

  Research on Adversarial Disturbance Based on Meteorological Time Series Data

  By Renjie Wang, Haizhong Liu, Yang Zhu

  Abstract: When the deep learning model is used to predict time series data, it is easy to be adversarially attacked. The time series data is sensitive to the abnormal disturbance and has strict requirements on the disturbance amount. To solve these problems, we propose to generate adversarial time series by adding disturbance terms to the original time series, and design an adversarial attack algorithm based on the importance measure (AAIM in …

  Published in Journal of Industrial Safety Engineering · Vol. 9, Issue 3, 2022 · pp. 1–19 Read article →