The Internet of Things (IoT) has developed a lot in recent years [1-2], and the Social Internet of Things (SIoT), a new application of IoT, is now evolving. The SIoT is a larger social network, connecting people and people, people and objects, and objects and objects. Using the perceptual monitoring technology of IoT, every building, car, or shopping mall can post a message automatically, realizing the interaction of people and a specific object. One part of SIoT can be a wireless sensor network (WSN), sensing the state of an object or monitoring an event in the network. Since SIoT enables interaction of an object with people or another object, there will be wireless communication between objects and people. In that case, The use of wireless communication media means that anyone with powerful radio transceivers can attack the network. Because of this vulnerability, SIOT faces security threats such as information eavesdropping, data fabricating, node compromising, and route disrupting. These network attacks threaten either content privacy, the confidential data of a message, or contextual privacy, information about the surrounding network. All these problems make privacy protection of the SIoT becomes essential. Wireless sensor networks (WSNs) show great application value for national security, military monitoring, health care, and environmental monitoring [3-5]. However, wireless network privacy issues have become the main bottlenecks for its further development. In this paper, we focus on protecting source location in a WSN related to SIoT. Location privacy is a typical context privacy issue. Particularly, an adversary can detect the message flow to determine the source node location and then attack the target of interest. This problem of source location privacy (SLP) has not been addressed effectively because it cannot be easily solved by encryption or authentication. Wireless sensor nodes have limited storage space, energy supply, and computing capacity. In order to preserve the location of the sensitive source node, we must develop a feasible and energy-efficient protocol to hide the source from being detected by adversaries. To clearly illustrate the SLP issue, we consider the classical “panda-hunter” model in Figure 1. A WSN can be deployed in a wildlife habitat to monitor pandas’ habits and behavior. Once a node detects a panda in its communication range, it becomes a source node and periodically sends report packets to the base station (Sink in Figure 1) by multi-hop wireless communications. Obviously, this scenario is unsafe for the source since the communication signal is exposed to the air. The hunters and poachers (Adversary in Figure 1) can use expensive devices to eavesdrop on the network, following the flow of packets, speculating the routing pattern and finally tracing back hop-by-hop to find the panda. Thus, hiding the location of a source node is a critical issue for WSNs.