## 1 Introduction  
Recently, unmanned aerial vehicle (UAV) techniques have been widely applied to wireless communication systems such emergency rescue, homeland security, etc., owing to the flexible and quick deployment. Researchers from academia, industry, government agencies, etc., have paid lots of attractions to UAV communications. Game theory has been adopted to deal with a smart attacker from UAV [1]. Traditional UAV network security studies generally assume UAV communications are authorized and rightful, so researchers put great efforts to preventing existing UAV communications form malicious attacks such as jamming and eavesdropping [2; 3; 4; 5]. However, the paradigm has changed with the development of UAV technologies. Terrorists or criminals may use UAVs to establish wireless communications for committing crimes and terrorism [6; 7]. For instance, the eavesdroppers in the UAV communication networks can overhear the secure message, thus improving the capacity of communication network by reporting faked channel state information on the basis of the continuously changing channel environments [8; 9]. More seriously, criminals can use UAV communication networks to commit bombing activities, and business spies may use them to filich trade secrets. In traditional UAV surveillance works, eavesdropping and jamming UAVs are usually static during their tasks, while in this paper, we consider the UAV's dynamic motion, which can reflect the performance of jamming selection on power consumption. The policy can provide the optimal results of eavesdropping and jamming selection based on power consumption in different locations. As shown in Figure 1, authorized UAVs share information through an existing UAV network, which may change topology occasionally because of UAV's unpredictable trajectory. The new infrastructure-free mobile communication can be easily used by malicious UAVs (marked as red ones), e.g., criminals, terrorists, and business spies, to commit crimes, jeopardize public safety, invade the secret database of other companies, etc., thus imposing new challenges on the public security [1]. Therefore, there is a growing need for government agencies to legitimately monitor and eavesdrop wireless communications of suspicious UAVs [8]. In particular, we consider four surveillance scenarios as shown in Figure 2, where a legitimate UAV, i.e., \(UAV_{L}\), aims to monitor a suspicious communication link from a suspicious UAV transmitter (\(UAV_{ST}\)) to a UAV receiver (\(UAV_{SR}\)) over fading channels. It is seldom to have significant multipath links in the sky. However, flying UAVs are strictly restricted according to policies. It is allowed for flying UAVs freely under some low altitudes, which are even lower than tall buildings, and what is more, extreme weather conditions may also influence the state of communication links for UAVs, so there are still scenarios for UAVs communication in multipath links. In reality, UAV transmitter and UAV receiver are relative, since communication links are bi-directional, using a pair of transmitter and receiver for simultaneous transmission in both directions. Figure 1: A malicious eavesdropping scenario where malicious unmanned aerial vehicles (UAV) attack authorized UAVs through the UAV network. Figure 2: Eavesdropping via jamming. In this scenario, we assume that the suspicious pair of UAVs (known as \(UAV_{ST}\) and \(UAV_{SR}\)) has been detected by authorized agencies at the beginning, and they are eavesdropped by a legitimate UAV monitor (\(UAV_{L}\)). Suspicious users' detection and association can be referred to in Reference [9]. We use the eavesdropping model proposed by [PERSON], et al. [10] which proactively generate jamming signals to interfere with the suspicious communication link through a full-duplex mode, so as to decrease the achievable data rate at the suspicious transmitter or receiver for overhearing more efficiently. In order to initialize investigation, we assume that no advanced anti-eavesdropping schemes for security are employed by suspicious UAVs.