## 2 Related Works  
In the literature, there have been a handful of methods for preventing existing wireless networks (e.g., cellular networks) from malicious attacking since wireless networks are prone to malicious attacks such as eavesdropping attack [12], DoS attack [14], spoofing attack [15], MITM attack [16], message falsification/injection attack [17], etc. For instance, authorized devices in a wireless network can, by interference, be illegal devices in the same network in terms of information stealing or virus attacking. Moreover, malicious device may overhear wireless communications sessions, as long as it is within the transmit coverage area of the transmitting device. Generally speaking, the requirements of confidentiality, availability, integrity, and authenticity should be satisfied by secure wireless communications [18]. Cryptographic techniques for preventing eavesdroppers from intercepting data transmissions between legitimate users are typically employed by existing communication systems, thus maintaining confidential transmission in wireless networks [19; 20]. For example, passive eavesdropping is applicable to intercept infrastructure-free wireless communications (e.g., UAV networks) [21]. Recently, physical-layer security has emerged as a promising solution to secure UAV communications against eavesdropping attacks [22; 23; 24; 25]. The authors in Reference [22] proposed an algorithm to adaptively control the UAV's location over time to optimize UAV's average secrecy rate basing on a secure single-UAV communication system. In Reference [23], authors regarded UAVs as friendly jammers to protect the ground wireless communication, while authors in References [24; 25] employed UAVs as mobile relays to facilitate secure or reliable wireless communications. Authors in [26] introduced a power allocation strategy which was regarded as a zero-sum game between the transmitter and the eavesdropper. In Reference [27], authors considered a power control strategy based on Q-learning for the transmitter to enhance the secure capacity via preventing from smart attacks in the dynamic game, however, authors in Reference [27] did not consider the practical channel estimation error, which should not be ignored in the practical communication scenarios, since it will give a significant impact on the network performance. The authors in Reference [28] proposed the optimal power allocation strategies by studying the impact of channel estimation error on the capacity of specific channels. Authors in Reference [29] proposed a theoretical communication scheme, which use multiple antennas to generate artificial noise to degrade the channel quality of eavesdroppers. In Reference [30], authors proposed a low-density parity-check protocol, which used a four-step procedure to ensure wireless information-theoretic security, to achieve communication rates close to the fundamental security limits in wireless communications. However, none of these works [22; 23; 24; 25; 26; 27; 28; 29; 30] consider the use of proactive eavesdropping to enhance network security. In order to enhance the quality of secure wireless transmissions, jamming the eavesdropper is an effective approach [31; 32; 33]. Authors in Reference [31] presented a cooperative jamming scheme, which help a legitimate user improve its data rate via sending a jamming signal to the eavesdropper. The authors in Reference [32] presented a hybrid artificial fast fading scheme, which achieved better performance for eavesdropper. In Reference [33], authors proposed a full-duplex scheme, which transmitted the jamming signal to degrade the channel of eavesdropper. Under this scheme, the system was no longer interference-limited, compared with the half-duplex case. Reference [34] formulated a stochastic game, and provided insights for secret and reliable communication against both jamming and eavesdropping. However, authors in References [31; 32; 33; 34] considered eavesdropping as an illegitimate attack and targeted on decreasing the eavesdropping performance.