## 1 Introduction  
The Internet of things (IoT) is the heart of Industry 4.0, where a number of smart devices are deployed on a communication network. The devices process the incoming and outgoing data ubiquitously, and they communicate among themselves autonomously. Thus, IoT is the crux in developing new applications and experiences including smart factories, smart agriculture, smart homes, etc. The smart devices of IoT play key roles in collecting, processing, and forwarding data from sources nodes to the sink node(s) via multiple hop network communication. This ubiquitous and autonomous communication results in Wireless Sensor Networks (WSNs) with new challenges that are related to their sustainability. On one hand, since these devices are of constrained capabilities such as energy supply, transmission, range, computing power, etc., lots of research works focus on developing routing methods that cope with these devices. On the other hand, these networks are typically deployed and operated in unattended environments. Therefore, these networks might be vulnerable to various type of attacks that may impact the operation of the network partially or completely, such as identifying the location of critical network nodes (such as source(s) and sink(s) nodes). Securing the location of critical nodes in WSNs is a complicated, pressing challenge that needs to be tackled on different fronts. The seminal work presented in [1] highlights the importance of the Location Privacy Preservation (LPP) of critical nodes in a WSN. Specifically, the authors depicted, via an example of Panda-Hunter Game, the importance of LPP. For example, a habitat containing pandas is monitored via many wireless sensor nodes that are randomly distributed across the habitat. The sensor (source) nodes monitor and send information about pandas to a base (sink) node. The information received at the base station can be used for the well-being of pandas in the habitat. On the other hand, a hunter is interested in identifying the location of pandas, which can be indirectly achieved by identifying the location of the source nodes. Thus, the hunter moves into the habitat and monitors the network traffic. Tracing the network communication packets (even without actually looking inside the packet) can reveal the location of the source nodes, thereby compromising the location of pandas. Thus, LPP routing methods are critical along with the packet encryption methods. In this work, we focus on improving routing methods under the assumption that the adversary (generalized term for the hunter in the above example) lacks the ability to decipher the encrypted packets. The conventional research on LPP in WSNs typically assumes a specific intrusion model, and the primary goal is to develop a corresponding routing method that is better in terms of location privacy. In addition to that, the secondary goals may include: reduced age of information and energy consumption. One of the naive assumptions in the conventional approaches is the prepossession of a specific intrusion model. Since the intrusion can be executed by one or more adversaries, surviving one or more intrusion techniques with one specific routing method may not be fruitful in preserving the location of the critical nodes over the network's time horizon. Motivated by the advent of network softwarization and advancements in the Soft Defined Network (SDN) and Network Functions Virtualization (NFV) [2; 3], our goal is to propose and develop a hybrid routing model where the network communications are carried out via multiple routing mechanisms. Such a tactile routing model provides the means to handle multiple intrusions via multiple techniques. Later, we discuss the applicability of this approach in real networks. The rest of the paper is organized as follows. Section 2 presents the relevant literature on WSN routing and attack mechanisms. The problem statement is established in Section 3. A connection between the proposed LPP problem and game theory is highlighted in Section 4.