A survey on location privacy protection in Wireless Sensor Networks

Highlights

• In this paper, we present a detail survey of existing Location Privacy Protection (LPP) techniques in WSNs.

• The adversary model, categories of LPP, and methods used in these techniques are carefully presented.

• Finally, we analyze and compare the performance of each technique.

Abstract

Location of sensor nodes is one of the most important and fundamental information for Wireless Sensor Networks (WSNs), because it provides basic support for many location-based applications (e.g., navigation and object tracking) and location-aware protocols (e.g., geographic location-based routing protocols). However, by extracting and analyzing the location information in packets, attackers can easily obtain the real position of source nodes or base station using hop-by-hop backtracking strategy, which is extremely harmful for the normal operation of sensor networks. So, we need to provide location anonymity for sensor networks. In this paper, we present a detail survey of existing Location Privacy Protection (LPP) techniques in WSNs. First, the network model, the attack model and the performance evaluation model are reviewed. Then, this survey provides a review of the literature about location privacy protection, which is classified into the following three categories: 1) source nodes' location privacy preserving, 2) sink nodes' location privacy preserving, and 3) location privacy preserving for both source and sink nodes. The details of location privacy preserving protocols are carefully analyzed, and the key mechanisms in each protocol are elaborated. In addition, the performance, including the network safety period, the packet transmission latency and the energy consumption, is analyzed and compared. Finally, the exiting problems and the future research issues are presented.

Introduction

Over the past few decades, WSNs have drawn considerable attention for many applications, environmental monitoring, disaster warning, traffic management, health care, emergency rescue, object tracking, etc., (Akyildiz et al., 2002; Qiu et al., 2017, 2018a, 2018b). In the applications, many tiny sensor nodes with small size and limited resources are randomly distributed in the monitoring environment to sense, collect information, then transmit collected data to the destination (a base station or a sink node) via multi-hop communication (Doohan et al., 2012). The sink nodes then aggregate and process the packets, and further transmit them to the users for different requirements (Tunca et al., 2014). However, WSNs are always deployed in unattended harsh environments and the wireless channel is open, thus the kind of multi-hop communication is vulnerable to a variety of malicious attacks, e.g., the location privacy disclosure. During the applications, the location is one of the most important and fundamental information. For example, in the multi-hop communication pattern, the location information is always used to build the optimal or shortest routing path (Cadger et al., 2013; Subramanian et al., 2007). Also, the location information can be used to provide many kinds of Location Based Service (LBS), e.g., navigation and object tracking. It should be noticed that while the LBS brings the users tremendous convenience, it also introduces the disclosure of location privacy, which seriously affects the application development of WSNs. For example, in the field of animal surveillance, by monitoring and backtracking the network traffic flow, or by compromising a common sensor node and analyzing the sensitive information in data packets, an attacker can easily find out the real position of source nodes, thus ultimately detect and catch rare animals, as shown in Fig. 1. Therefore, research on location privacy preserving technology is of great significance for large-scale applications of WSNs.

In the research of location privacy preserving, a network model and an attack model are first designed. Based on the network model and the attack model, different location privacy preserving technologies have been thoroughly studied to effectively avoid the leakage of network sensitive position information, e.g., the position of source nodes or base stations. In addition, the network energy consumption, the communication delay, the data query precision and reliability, are also needed to be considered in the location privacy protection technologies. Thus, an evaluation model is required to evaluate the performances of different privacy preserving technologies.

In Ozturk et al. (2004), the Panda-Hunter Game is first proposed for location privacy preserving, which makes the scenario of location privacy much more clear. As shown in Fig. 1, in the Panda-Hunter Game model, many small sensor nodes are randomly distributed in the habitat to monitor pandas. Once a panda appears, the surrounding sensor nodes (which are named source nodes) will quickly monitor it and send information (e.g., the position of the panda) to the sink via multi-hop communication or routing paths. Also, there is a hunter in the Panda-Hunter Game, which is able to move freely in the network and monitor the local wireless communication. By monitoring the network traffic and tracing back the routing paths, the hunter can find out the exact position of source nodes and finally find the panda. In this research, the position privacy preserving technologies are needed to prevent the hunter to find the position of real sources while ensuring the normal transmission of panda monitoring data.

Privacy is a critical issue in field of WSNs. Many algorithms and techniques have been studied to protect location privacy in WSNs, e.g., encryption algorithm (Agrawal et al., 2003) and anonymous mechanism (Sweeney, 2002), which are efficient for protecting the information security. However, they cannot well protect the location privacy, especially under internal attacks. For example, if an adversary compromises a sensor node and retrieves private keys, it can easily decrypt the information, track back the network traffic and find source nodes' position. Therefore, we need to study new protocols for sensor nodes' location privacy preserving. However, in WSNs, the characteristics of limited resources, self-organization, multi-hop communication and so on, which bring great challenges for the study of location privacy preserving:

• Sensor nodes are powered by batteries, thus the energy resource is very limited. Excessive energy consumption has a significant impact on the network's performance or even shortens the network lifetime. Therefore, the method of location privacy protection with high throughput or high energy consumption is not suitable for WSNs.

• Due to the small size and the low cost requirements, the storage space and the computing power of sensor nodes are limited. Thus, they are unable to carry out a large amount of data storage or complex operations. Therefore, the method of location privacy protection with high storage requirement or high computational complexity is not suitable for WSNs.

• The limited transmission distance of sensor nodes needs multi-hop communication to transmit packets from source to destination nodes which can lead to unbalanced network traffic. That is, a sensor node closer to the destination has higher traffic load, since it needs to not only transmit its own generated packets but also route packets from the nodes multi-hop away from the sink node. The unbalanced network traffic makes an adversary easily identify the source nodes or the base stations.

• WSNs are often deployed in unattended environments and face different kinds of malicious attacks, in which an attack can launch physical attacks to capture legal sensor nodes, and further obtain the private cryptographic keys used for secure communication. Using the private keys, the attack can decrypt any communication in the network and easily get the location privacy. In addition, different kinds of attacks need different kinds of protection mechanisms and different applications have different protection requirements, which make it more difficult for location privacy preserving in WSNs.

The location privacy preserving for WSNs is first studied in Ozturk et al. (2004), and has received widespread concern in recent years. In George and Nathaniel (2012), the location privacy protection techniques in WSNs against a local eavesdropper are summarized. However, the techniques against global attacks are not discussed in this survey paper. In Liang et al. (2013), the key problems of location privacy protection are analyzed, including the model of privacy protection, the anonymous model and the system architecture. However, few location privacy protection techniques is analyzed in the paper. In Conti et al. (2013), a detail survey of source location privacy is provided, while the problem of sink node location privacy is not included. In Zurbarn et al. (2014), the privacy in location-based services is researched. However, the discussed techniques such as the cryptography-based protocols are not suitable for WSNs. In Dhivya and Siddique (2014), a survey on location privacy protection of both source and sink nodes is presented, while only an apart of location privacy protection techniques are discussed. In Zhang et al. (2015) and Grissa et al. (2017), the privacy preservation problem in cognitive radio networks is studied. In Gupta and Prince (2017), the source location privacy protection techniques based on random walk are surveyed. Compared with the above mentioned existing survey paper, our paper provides a comprehensive overview of location privacy protection, including the basic conception, the network model, the attack models including local and global eavesdroppers, and the different techniques for both source and sink nodes.

This paper provides a systematic summary of existing position privacy protection research for WSNs. In accordance with the protection target, the existing research works are classified into the following three categories: 1) source location privacy preserving, 2) sink node location privacy preserving, and 3) location privacy preserving for both source and sink nodes. The core technologies in each protocol are described in detail and the specific attacks that each protocol can resist are compared. The advantages and disadvantages of each protocol are analyzed, and future research directions are listed and discussed.

The rest of this article is organized as follows: Section 2 describes the network model, the attack model and the performance evaluation model. Section 3 Source location privacy preserving, 4 Sink node location privacy preserving, 5 Location privacy preserving for both source and sink nodes review the three categories of existing location privacy preserving research. Section 6 presents the detail comparison of each kinds of protocol, analyzes existing problems and future research issues about location privacy preserving. Finally, conclusions are given in Section 7.