Elsevier

Pervasive and Mobile Computing

Volume 40, September 2017, Pages 611-627
Pervasive and Mobile Computing

Signaling game based strategy for secure positioning in wireless sensor networks

https://doi.org/10.1016/j.pmcj.2017.06.025Get rights and content

Abstract

Sensor localization is demanded by wireless sensor networks, since the collected sensor data are meaningless if the position of the generating sensor is not available. The traditional approach of using GPS for location determination is not suitable for sensor networks, due to the increased costs and resource usage. For this reason, sensors exchange Radio Frequency messages, so as to measure their respective distances and determine their locations by means of multilateral triangulation with sensors of known positions, called anchors. Such an approach, however, is particularly vulnerable to several kinds of attacks aiming at causing wrong position estimations with a malicious intention. Such attacks can be tolerated with proper countermeasures, belonging to the so called secure localization, but this is achieved at the expenses of high costs in terms of exchanged messages and exhausted sensor resources, such as the battery. For these reasons, it is crucial to use the secure localization only when needed in order to extend considerably the life span of the sensors. Therefore, we propose to model the interaction of an anchor with a sensor as a signaling game, and to use such a formalization to discipline the use of secure positioning methods based on the received messages from the anchors. We have proved with simulations that such a solution is more efficient than a naive one of always applying secure localization.

Introduction

Currently, context-awareness [1], [2] is a strategic feature of smart applications available in our smartphones, or belonging to the up-coming vision of the Internet-of-Things (IoT), since it allows the applications to adapt their behavior and/or the provided information accordingly to their context of execution. Context-aware systems constitute an unmissable and valuable component of a ubiquitous and/or pervasive computing environment. The context can be defined according to different aspects and features, and the literature presents a variety of context formulations of an execution context for an application, but in any of these formulations we can always find that location is a primary component. Therefore, it is of pivotal importance for these applications to achieve the ability of a hosting device to determine its exact location in terms of the geographic coordinates within a given building (indoor positioning) or open-air environments (outdoor positioning). In the current and upcoming software platforms for smart environments, we are witnessing the progressive proliferation of location-sensitive applications also due to the fact that the information that they generate may be meaningless if a location is not tagged to them. Apart from the issue of user localization, which has been successfully resolved by means of satellite positioning technologies such as Global Positioning System (GPS) [3], there is a strong demand of effective and efficient solutions for positioning of tiny devices forming the so-called Wireless Sensor Networks (WSN) [4], supporting the future applications of IoT. If we consider the applications that are being developed under the umbrella of the smart city buzzword, localizing sensors within a given WSN is a crucial requirement in real scenarios. In facts, sensors can exchange geographically meaningful data by requiring the exact localization of the producing sensor. Let us consider the case of a WSN used for environmental monitoring, e.g., controlling the occurrence of fire within a forest. The mere information of the presence of fire is not useful if it is not correlated with the information on where such fire is present. This is made by attaching to the exchanged messages the location of the sender, e.g., the sensor that detected the fire. Moreover, the location information of sensors can be used in certain routing algorithms relying on a geographic approach to perform proper optimizations [5] : such algorithms consider position information to forward the data towards certain regions rather than the whole network so as to lower the generated network load.

Localization algorithms within the context of WSN strongly focus on two key principles: minimizing the battery consumption and avoiding the use of extra hardware. For this reason, several algorithms proposed in the literature are based on the Received Signal Strength Indicator (RSSI) rather than GPS [6], since this indicator is usually provided for free in almost all the radio chips adopted nowadays, without requiring any special hardware. RSSI-based positioning within a WSN is based on measuring the signal fading due to the covered geographical distance, and determining the difference in the distances to a given set of nodes at known locations that broadcast signals at known times by applying the so-called multilateral triangulation [6]. The WSN positioning is still considered an open issue due to the inaccuracy issues affecting the RSSI-based methods, due to multi-path fading and shadowing phenomena, and the current research is active in finding solutions in order to promote the accuracy and precision of these methods. However, such research is mostly conducted in non-hostile environments, where the only factors influencing a worsening of the positioning quality is due to the attenuation phenomena of the RF signals exchanged by the node on the WSN. Another research path related to the WSN positioning is the one concerning the security aspects, which are pivotal in the beforehand mentioned smart application. In fact, the available RSSI-based methods have been proved to be vulnerable [7], by impersonating nodes and distance compromising through delaying or speeding-up attacks, so that an adversary may perform location spoofing. Spoofing a node position means that an attacker convinces that a node is located at a different location than the real one. In an application for environmental monitoring, such kind of attack may have the consequences of slow down the action of the fire brigades, since they may be deployed in the wrong locations were a fire is not placed, or may be leaded unprepared to areas where the fire is particularly aggressive and persistent.

Secure positioning [7] consists in a series of techniques in order to prevent the spoofing a node position, and provide guarantees on the trustworthiness of a location information. Such techniques deals with two complementary aspects: secure location and location verification. On the one hand, the first aspect consists in enforcing a given positioning methods by solving their intrinsic vulnerabilities so as that an adversary may not be able to commence an attack and compromise the positioning system. On the other hand, the second aspects is related to the fact that a node may not trust the reported location of another node and may start actions in order to verify it. The current literature is characterized by a set of methods for outlier detection, node filtering and prevention of erroneous distance measures for realizing one of both these two mentioned aspects. Despite secure positioning does not require special hardware, its execution is not convenient for a WSN, since a node needs to perform proper actions for secure positioning that implies an increase in the energy consumption. A more efficient solution is to strategically use secure positing only when needed, so as to optimize the energy consumption and still achieve secure guarantees on the location information.

Our work aims to deal with this problem by employing game theory for the modeling of the interaction of the nodes when location needs to be determined. We have used a signaling game to model the message exchanges of a node with another one with known location, and to decide what to do after such a message has been received and the trustworthiness of the contained data is questioned. Our intent is to find when secure positioning techniques are needed to be executed by keeping a low energy usage profile. This is novel with respect to past application of game theory within the context of secure localization. For example, game theory has been previously used within the context of Verifiable Multilateration in [8] by using a non-cooperative two-player game to determine the best placement for the verifiers within a WSN and increase the capability of securely localizing malicious nodes. On the contrary, we have used a game theoretic approach in estimating when it is needed to trigger a secure localization mechanism due to the low reputation of an anchor and the questionable trustworthiness of the received location information. Such a strategic activation of the security mechanism only when needed is able to lower the consequent costs in terms of energy usage by sensors. This is a progress with respect to the current literature on this topic where the security mechanism were never activated, since the operational conditions were considered trusted and secure, or always activated all the time, since the conditions were considered always hostile.

This paper is organized as follows. Section 2 introduces the current literature on localization algorithms in WSN, while Section 3 highlights the flaws of positioning systems with respect to the security requirements and introduces the current literature on secure positioning in WSN. Such a section also describes briefly the problem we intend to resolve. Section 4 contains a description of the use of signaling game for secure positioning, which is qualitative and quantitative evaluated in Section 6. We conclude in Section 7 with lesson learnt and final remarks.

Section snippets

Localization techniques

Localization is considered a key feature for several kinds of context-aware services running within the context of sensor networks, such as vehicle tracking, environmental and habitat monitoring, and health care. Such services typically obtain location-related information from the implementations of proper methods, which provides the device position based on inputs coming from the hardware available at the running node. There is a rich literature on these methods, which has been presented and

Secure positioning in wireless networks

As mentioned the determination of the accurate and precise location of a sensor within a WSN is a critical task and can strongly influence the effectiveness and efficiency of the sensing applications built on top of the deployed WSN. The inaccuracy of a localization system is typically caused by the variability of the measured features of the workspace, such as distances and RSSI values. This is due to the fact that RF signals reduce their intensity not only due to the covered geographical

A signaling game between an anchor and an unlocated sensor

As illustrated by Fig. 4, we can assume that during an RSSI-based localization method, the node to be localized receives certain messages from an anchor, containing the known location of the sender and its output gain for the emitting antenna. The sensor has to measure the RSSI value for the received messages, so that to estimate the distance to the anchor. A threat to this scheme is a false value for the anchor’s location or the output gain of its antenna. The problem to be resolved is when to

Pure strategy equilibria

An initial analysis of our game can be made by using the concept of Nash equilibrium within the context of games with imperfect information or Bayesian games. If we assume that a player has a set of possible strategies, and each has associated a given payoff, then a Nash Equilibrium (NE) is given by the strategies that maximize the achievable payoff, so that it is not profitable to take another strategy. More formally, sS:cP,xY,πc(sc,sc)πc(x,sc)sis a Nash equilibriumwhere s denotes

A game theoretic algorithm for anchor-sensor signaling

We can use the introduced formulation of the anchor-sensor signaling game and the consequent analysis in order to determine the proper algorithm for disciplining the interactions underlying the correct localization of sensors within a WSN. By considering the Pure Strategy Equilibria, the naive solution is to always trust a c signal, and to always challenge a d signal. However, this is not an optimal one since challenging a d signal when an anchor is honest implies a waste of resources by the

Conclusions

Sensor localization is of pivotal importance so as to provide a valuable context to the exchanged sensor data and to better processing them. For this reason, sensors should be equipped with methods to determine their position, without requiring additional hardware. Despite being less accurate, positioning solutions based on the RF signals are preferred for sensors. However, such solutions are particularly vulnerable to different kinds of attacks, that are able to compromise the positioning

Acknowledgment

This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning under Grant 2015R1C1A1A02037515.

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