Location Verification System Research Articles

A More General Information Theoretic Study of Wireless Location Verification System

In recent years, the issue of location verification system (LVS) has received significant attention in wireless communication networks, especially in Intelligent Transportation Systems (ITSs) and vehicular technology, where the location information is important for users' safety and security. In this article, we consider a vehicular network and analyze a more general Information Theoretic (ITc) study of LVS, specifically, aiming at finding an optimum decision threshold for detection a spoofed location and increasing the system ability in correctly detecting malicious users. For this purpose, we propose different information theoretic measures (Renyi divergence, Renyi mutual information, Kullback-Leibler divergence, Kullback-Leibler mutual information and Jensen-Shannon divergence) for identifying malicious user. Simulation results and comparison between proposed measures show that the optimum decision threshold can be achieved by applying the Jensen-Shannon divergence measure.

Location Verification for Emerging Wireless Vehicular Networks

The work reported here utilizes the best aspects of information theory and deep-learning concepts so as to provide, for the first time, a solution for a real-world location verification system (LVS) in the context of vehicular networks. it is well established that global positioning system coordinates supplied by vehicles will be a vital component of such emerging networks. This supplied location information, if erroneous and not verified, can seriously degrade the overall system performance and lead to significant safety issues. A number of location verification protocols and systems have been developed to address this important problem but all have operational constraints and performance limitations due to their requirement for ideal static channel conditions and assumed threat models. In this article, we remove such limitations by designing a neural-network-based LVS (NN-LVS) that can accommodate a priori unknown channel conditions and unknown threat models. Under most channel conditions, the NN-LVS shows a performance improvement of 50%, or more, relative to other LVSs. We also derive a new information-theoretic bound on the total error for an LVS and show how this new bound allows for a useful tradeoff in learning-time versus verification-performance for the NN-LVS. We demonstrate an improved performance for the NN-LVS within the context of vehicular networks using time of arrival measurements of the vehicles’ transmitted signals measured at multiple verifying base stations. The work reported here, we believe, paves the way to the actual deployment in real-world conditions of LVSs for emerging vehicular networks.

Exploiting Radio Irregularity for Location Verification in Sparse MANETs

Traditional distance-based location verification system (LVS) is ineffective for some attacks in sparse mobile ad hoc networks, e.g., the similar distance-based malicious (SDM) attack. In this letter, we propose to exploit radio irregularity to build a novel LVS. Our system detects attack based on the estimated difference of radio irregularity coefficients and the claimed locations of the malicious node and an assistant node. To the best of our knowledge, our system is the first-of-its-kind that can detect SDM attack and pollution attack with only the received signal strength indicator information transmitted by a detecting node to the suspicious malicious node and an assistant node. Simulation results demonstrate that our proposed system can detect the attacks that cannot be detected by traditional distance-based methods.

Location Verification Systems Under Spatially Correlated Shadowing

The verification of the location information utilized in wireless communication networks is a subject of growing importance. In this work we formally analyze, for the first time, the performance of a wireless Location Verification System (LVS) under the realistic setting of spatially correlated shadowing. Our analysis illustrates that anticipated levels of correlated shadowing can lead to a dramatic performance improvement of a Received Signal Strength (RSS)-based LVS. We also analyze the performance of an LVS that utilizes Differential Received Signal Strength (DRSS), formally proving the rather counter-intuitive result that a DRSS-based LVS has identical performance to that of an RSS-based LVS, for all levels of correlated shadowing. Even more surprisingly, the identical performance of RSS and DRSS-based LVSs is found to hold even when the adversary does not optimize his true location. Only in the case where the adversary does not optimize all variables under her control, do we find the performance of an RSS-based LVS to be better than a DRSS-based LVS. The results reported here are important for a wide range of emerging wireless communication applications whose proper functioning depends on the authenticity of the location information reported by a transceiver.

Information-Theoretic Location Verification System With Directional Antennas for Vehicular Networks

In this paper, we consider a vehicular network and propose the application of directional antennas to a recently proposed information-theoretic location verification system (LVS), aiming at increasing the system capability in correctly detecting malicious nodes. In the proposed LVS with directional antennas (LVS-DA), we adopt a more realistic dual-slope large-scale fading model that is suitable to vehicular networks. The performance of the proposed scheme is evaluated analytically for some specific number of directional antennas and confirmed by numerical results, showing that the proposed LVS-DA scheme is capable of considerably increasing the system capability in detecting malicious nodes when compared with other recently proposed schemes, under different scenarios.

Optimal Information-Theoretic Wireless Location Verification

We develop a new location verification system (LVS) focused on network-based intelligent transport systems (ITSs) and vehicular ad hoc networks (VANETs). The system that we develop is based on an information-theoretic framework in which the mutual information between the system's input and output data is maximized. Our system takes as inputs a user's claimed location and base station (BS) received signal strength (RSS) measurements to form an optimal decision rule on the legitimacy of the claimed location. The scenario that we consider is where a noncolluding malicious user alters his transmit power in an attempt to fool the LVS. We develop a practical threat model for this attack scenario and investigate the performance of the LVS in terms of its input/output mutual information. We show how our LVS decision rule can be straightforwardly implemented with a performance that delivers near optimality under realistic threat conditions. The practical advantages that our new information-theoretic scheme delivers, relative to more traditional Bayesian verification frameworks, are discussed.

WiLoVe: A WiFi-coverage based Location Verification System in LBS

With the proliferation of mobile devices, location-based services (LBS) have penetrated into our daily life in recent years. In an LBS system, the users check in at different venues to acquire rewards such as virtual points or real-world coupons/discounts, and easily share with their friends the recent activities. While these rewards benefit benign users a lot, they are incentives for malicious users to cheat on their locations. Recent researches have revealed that location cheating can be launched automatically on a large scale at ease. In current practice, the defense against location cheating relies on the server side solution, which has been proven to be insufficient. In this paper, we propose a novel verification system named WiLoVe. It maps the physical area of a venue to the local WiFi coverage and involves the venue owner as the verifier, hence utilizes the user's capability of one-hop communication with the verifier to verify the user's presence at the venue. In this work, we implement the verifier as an independent application, which can easily be installed on the venue owner's existing devices (laptops, cellphones, etc.). Hence, no additional hardware is needed. An adaptive algorithm is designed to defend against proxy attacks based on the check-in delay. Extensive experiments show that WiLoVe achieves low false rate, as well as consistent user experience, acceptable power consumption, and good applicability to different WiFi environments.

Lightweight Location Verification Algorithms for Wireless Sensor Networks

The knowledge of sensors' locations is crucial information for many applications in Wireless Sensor Networks (WSNs). When sensor nodes are deployed in hostile environments, the localization schemes are vulnerable to various attacks, e.g., wormhole attack, pollution attack, range enlargement/reduction attack, and etc. Therefore, sensors' locations are not trustworthy and need to be verified before they can be used by location-based applications. Previous verification schemes either require group-based deployment knowledge of the sensor field, or depend on expensive or dedicated hardware, thus they cannot be used for low-cost sensor networks. In this paper, we propose a lightweight location verification system that performs both “on-spot” and “in-region” location verifications. The on-spot verification intends to verify whether the locations claimed by sensors are far from their true spots beyond a certain distance. We propose two algorithms that detect abnormal locations by exploring the inconsistencies between sensors' claimed locations and their neighborhood observations. The in-region verification verifies whether a sensor is inside an application-specific verification region. Compared to on-spot verification, the in-region verification is tolerable to large errors as long as the locations of sensors don't cause the application to malfunction. We study how to derive the verification region for different applications and design a probabilistic algorithm to compute in-region confidence for each sensor. Experiment results show that our on-spot and in-region algorithms can verify sensors' locations with high detection rate and low false positive rate. They are robust in the presence of malicious attacks that are launched during the verification process. Moreover, compared with previous verification schemes, our algorithms are effective and lightweight because they do not rely on the knowledge of deployment of sensors, and they don't require expensive or dedicated hardware, so our algorithms can be used in any low-cost sensor networks.

Location verification using bidirectional one-way hash function in wireless sensor networks

Evolving networks of wireless ad hoc sensing nodes have many attractive applications. Localisation, that is to determine where a given node is physically located, is a key enabler for many applications of sensor networks. As sensor networks move closer to extensive deployments, security becomes a major concern, resulting in a new demand for secure localisation and location proving systems. We propose a secure localisation system based on a secure hop algorithm. A location verification system that allows the base station to verify the location claims of sensor nodes is also presented. It prevents a node from falsifying reported location information and can be used for location-based access control. In order to support the resource-constrained sensor nodes, the proposed approach makes use of efficient one-way hash functions. Finally, we report the evaluation of the secure localisation system. The proposed scheme performs well under a range of scenarios tested and is resilient against an attacker creating incorrect location information in other nodes.

A location tracking and verification system for the clinical environment

A location tracking and verification system for the clinical environment