Research Article
A Survey of Adversarial Attacks on Wireless Communications
@INPROCEEDINGS{10.1007/978-3-031-04231-7_7, author={Xiangyu Luo and Quan Qin and Xueluan Gong and Meng Xue}, title={A Survey of Adversarial Attacks on Wireless Communications}, proceedings={Edge Computing and IoT: Systems, Management and Security. Second EAI International Conference, ICECI 2021, Virtual Event, December 22--23, 2021, Proceedings}, proceedings_a={ICECI}, year={2022}, month={5}, keywords={Wireless communication Adversarial attack Deep neural network Machine learning}, doi={10.1007/978-3-031-04231-7_7} }- Xiangyu Luo
Quan Qin
Xueluan Gong
Meng Xue
Year: 2022
A Survey of Adversarial Attacks on Wireless Communications
ICECI
Springer
DOI: 10.1007/978-3-031-04231-7_7
Abstract
As the deep neural network (DNN) has been applied in various fields in wireless communications, the potential security problems of DNNs in wireless applications have not been fully studied yet. In particular, DNNs are highly vulnerable to malicious disturbance, which opens up opportunities for a small scale of adversarial attacks to cause chaos in the model's performance. This paper enumerates the main over-the-air attack mechanisms that threaten a wide range of existing defenses. For each type of attack, we introduce the working principle and list some of the latest applications in different wireless communication fields. With the threats of various attacks to a wide range of existing defenses shown, we hope to raise awareness of the lack of novel defense mechanisms.
