Adversarial training of LSTM-ED based anomaly detection for complex time-series in cyber-physical-social systems

Haiqi Zhu, Shaohui Liu, Feng Jiang

Abstract: Highlights•Solving the time-series anomaly detection problem in CPSSs by deep learning approach.•Combining the advantages of LSTM and reconstruction models for time- series anomaly detection problems.•Proposing the adversarial training method to improve the robustness of encoder-decoder model.•Avoiding the heavy workload of traditional methods for a priori knowledge and quality labeling.•Conducting the extensive experiments to prove the validity of the method in this paper.