Towards Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms. (arXiv:2207.09572v1 [cs.LG])

As deep learning models have gradually become the main workhorse of time
series forecasting, the potential vulnerability under adversarial attacks to
forecasting and decision system accordingly has emerged as a main issue in
recent years. Albeit such behaviors and defense mechanisms started to be
investigated for the univariate time series forecasting, there are still few
studies regarding the multivariate forecasting which is often preferred due to
its capacity to encode correlations between different time series. In this
work, we study …

adversarial attacks defense lg