## 1 Introduction  
As an important part of the Internet of Things (IoT), Wireless Sensor Networks (WSNs) are widely used in civilian and military applications. A WSN is composed of two kinds of nodes, namely, the sensor node and the sink node (SN). The sensor node acts as an information source, sensing the existence of objects and transmitting data packets to the SN by communicating with adjacent nodes wirelessly. The sink node is a powerful node with high performance, that is, it has unlimited computing capacity, storage capacity and energy resources. The SN is used to collect all the information sensed by the sensor nodes [1]. In the monitoring task-driven WSN, sensor nodes sense the existence of monitored objects in their sensing region, the node closest to the monitored target is called the source node (SoN). Anytime, any sensor node may become a SoN. Once the target is detected, the SoN will generate the encrypted data packets and transmit them to the SN in a multi hop fashion [2; 3]. However, due to the open nature of the wireless transmission medium, the packet sender can easily be located by the adversary. Therefore, although the enemy cannot obtain the content of the encrypted data packets, he can reversely go to the actual source nodes via hop-by-hop tracking along the routing path of the packets [4]. If the adversary gets the location of the actual source node, he can capture the protected objects, which may lead to unpredictable consequences. For example, a very important application of WSN is monitoring valuable objects or personnel. When a large number of sensor nodes are deployed in the field to monitor precious animals (such as pandas, South China tigers, and golden monkeys), the locations of the animals should not be learned by poaching. Similarly, on the battlefield, the location of the soldier should not be tracked by the enemy. In the process of monitoring these objects or personnel, it is necessary to protect the safety of the target while obtaining valid information. Therefore, the physical location privacy protection of the source node in WSN becomes a critical problem worthy to be studied. Source node location privacy protection is the process of keeping the location of a source node hidden from adversaries in a target monitoring network [5]. [PERSON] et al. first considered the source node location privacy problem of WSN in Reference [6], using Panda-Hunter game model, and based on this model they proposed to use a fake source called phantom node (PN) to entice the adversaries away from the actual source node [7]. In their Panda-Hunter model, shown in Figure 1, the monitored target is Panda, which is high-value and needs protection. In 2003, a single piece of panda fur was sold in Chongqing, China for $66,500 [8]. In Figure 1, a large number of sensor nodes are deployed in the field by the Save-The-Panda Organization to monitor the habitats of the panda [9]. Once the panda pops up, the sensor node closest to the panda becomes the SoN. The SoN generates the data packets and transmits them to the SN periodically via multi-hop routing techniques. The hunter (also featured as the adversary or attacker) starts at the sink node. He waits until he hears a packet. Once he hears a data packet, he can determine the packet sender via wireless locating technology [10] and quickly move to its location. By this way, the attacker can backtrack the routing path hop-by-hop to the SoN where the Panda is and capture the panda. In Figure 1, no source node location privacy protection technology is adopted, so the panda can be easily tracked and captured by the hunter. Therefore, the source location privacy protection technology must be used to prevent the hunter from locating the SoN, while ensuring that the data packets can be transmitted to the sink node. Figure 1: The Panda-Hunter model without privacy protection.