A causality adversarial attack generation algorithm was proposed in response to the causality issue of gradi-ent-based adversarial attack generation algorithms in practical communication system.The sequential input-output fea-tures and temporal memory capability of long short-term memory networks were utilized to extract the temporal correla-tion of communication signals while satisfying practical causality constraints,and enhance the adversarial attack perfor-mance against unmanned communication systems.Simulation results demonstrate that the proposed algorithm outper-forms existing causality adversarial attack algorithms,such as universal adversarial perturbation,under identical conditions.
关键词
智能通信系统/对抗攻击/深度学习/因果系统/长短期记忆网络
Key words
intelligent communication system/adversarial attack/deep learning/causal system/long short-term memory network
维普
万方数据