Location Proof Research Articles

PASPORT: A Secure and Private Location Proof Generation and Verification Framework

Recently, there has been a rapid growth in location-based systems and applications in which users submit their location information to service providers in order to gain access to a service, resource, or reward. We have seen that in these applications, dishonest users have an incentive to cheat on their location. Unfortunately, no effective protection mechanism has been adopted by service providers against these fake location submissions. This is a critical issue that causes severe consequences for these applications. Motivated by this, we propose the Privacy-Aware and Secure Proof Of pRoximiTy (PASPORT) scheme in this article to address the problem. Using PASPORT, users submit a location proof (LP) to service providers to prove that their submitted location is true. PASPORT has a decentralized architecture designed for ad hoc scenarios in which mobile users can act as witnesses and generate LPs for each other. It provides user privacy protection as well as security properties, such as unforgeability and nontransferability of LPs. Furthermore, the PASPORT scheme is resilient to prover–prover collusions and significantly reduces the success probability of Prover–Witness collusion attacks. To further make the proximity checking process private, we propose P-TREAD, a privacy-aware distance bounding protocol and integrate it into PASPORT. To validate our model, we implement a prototype of the proposed scheme on the Android platform. Extensive experiments indicate that the proposed method can efficiently protect location-based applications against fake submissions.

A privacy preserving of location proof updates through stamp

Area based administrations are rapidly winding up massively mainstream. Notwithstanding administrations dependent on clients' present area, numerous potential administrations depend on clients' area history, or on the other hand their spatial-transient provenance. Poisonous customers may lie about their spatial-transient provenance without a definitely arranged security structure for customers to exhibit their past zones. Right now, present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) contrive. STAMP is expected for extraordinarily delegated flexible customers making zone proofs for each other in a passed-on setting. In any case, it can without a lot of a stretch oblige trusted in adaptable customers and remote ways. STAMP ensures the uprightness and non-transferability of the zone proofs and makes sure about customers' assurance. A semi-trusted in Certification Authority is used to proper cryptographic keys and moreover watch customers against understanding by a light-weight entropy-based trust evaluation approach. Our model utilization on the Android organize exhibits that STAMP is ease similar to computational and limit resources. Wide diversion tests exhibit that our entropy-based trust show can achieve high understanding distinguishing proof precision.

Blockchain for secure location verification

In location-sensitive applications, dishonest users may submit fake location claims to illegally access a service or obtain benefit. To address this issue, a number of location proof mechanisms have been proposed in literature. However, they confront various security and privacy challenges, including Prover–Prover collusions (Terrorist Frauds), Prover–Witness collusions, and location privacy threats. In this paper, we utilize the unique features of the blockchain technology to design a decentralized scheme for location proof generation and verification. In the proposed scheme, a user who needs a location proof (called a prover) broadcasts a request to the neighbor devices through a short-range communication interface, e.g. Bluetooth. Those neighbor devices that decide to respond (called witnesses) start to authenticate the requesting user. We integrate an incentive mechanism into the proposed scheme to reward such witnesses. Upon successful authentication, a transaction is generated as a location proof and is broadcast onto a peer-to-peer network where it can be picked up by verifiers for final verification. Our security analysis shows that the proposed scheme achieves a reliable performance against Prover–Prover and Prover–Witness collusions. Moreover, our prototype implementation on the Android platform shows that the proposed scheme outperforms other currently deployed location proof schemes.

Decentralized proof of location in vehicular Ad Hoc networks

Future cooperative transportation systems will be highly dependent on correct situation awareness that can be established with the help of inter-vehicular communication. Location information from surrounding vehicles will most likely be used in such systems to make automated driving decisions, making it essential to guarantee location assurance. In this paper we propose Vouch+, which provides a scheme to improve trustworthiness of shared location information. The proposed scheme uses cryptographic primitives and mobility awareness to enable location proofs that work also in high-speed scenarios. Vouch+ takes a decentralized approach to establish trust in location information, but can also be used with future 5G infrastructure. The evaluation of Vouch+ using a synthetic dataset from the city of Cologne shows that using a decentralized approach is viable for cases where traffic is dense enough. In addition, simulation-based experiments show that Vouch+ is able to handle the high-mobility environment of vehicular networks and can counteract studied position-based attacks using reaction strategies.

Anchor of trust: towards collusion-resistant trusted indoor location for enterprise and industrial use

Reliable location estimation has been a key enabler of many applications in the UbiComp space. Much progress has been made on the development of accurate of indoor location systems, which form the foundation of many interesting applications, particularly in consumer scenarios. However, many location-based applications in enterprise settings also require addressing another facet of reliability: assurance. Without having strong guarantees of a location estimate’s legitimacy, stakeholders must explicitly balance the advantages offered with the risks of falsification. In this space, there are two key threats: replay attacks, where signal and sensor information is collected in one location and replayed in another to falsify a location estimation later in time; and wormhole attacks, where signal and sensor information is forwarded to a remote location by a colluding device to falsify location estimation in real-time. In this work, we improve upon the state of the art in wormhole-resistant location estimation techniques. Specifically, we present the Location Anchor, which leverages a combination of technical solutions and social contracts to provide high-assurance proofs of device location that are resistant to wormhole attacks. Unlike existing work, the Location Anchor has minimal hardware costs, supports a rich tapestry of applications, and is compatible with commodity smartphone and tablet platforms. We show that the Location Anchor can extend existing replay-resistant location systems into wormhole-resistant location systems, even in the face of very aggressive attacker assumptions. We describe the protocols underlying the Location Anchor, as well as report on the efficacy of a prototype implementation.

Lightweight Privacy Preservation for Securing Large-Scale Database-Driven Cognitive Radio Networks with Location Verification

The database-driven cognitive radio networks (CRNs) are regarded as a promising approach to utilizing limited spectrum resources in large-scale Internet of Things (IoT). However, database-driven CRNs face some security and privacy threats. Firstly, secondary users (SUs) should send identity and location information to the database (DB) to obtain a list of available channels, such that the curious DB might easily misuse and threaten the privacy of SUs. Secondly, malicious SUs might send fake location information to the DB in order to occupy channels with better quantity in advance and so gain benefits. This might also cause serious interference to primary users (PUs). In this paper, we propose a lightweight privacy-preserving location verification protocol to protect the identity and location privacy of each SU and to verify the location of SUs. In the proposed protocol, the SU does not need to provide location information to request an available channel from the DB. Therefore, the DB cannot get the location information of any SU. In the proposed protocol, the base station (BS) selects some SUs as witnesses to generate location proofs for each other in a distributed fashion. This new witness selection mechanism makes the proposed protocol reliable when a malicious SU generates fake location information to cheat the BS and also prevents SU-Witness collusion attacks. The results also show that the proposed protocol can provide strong privacy preservation for SUs and can effectively verify the location of the SUs. The security analysis shows that the proposed protocol can resist various types of attacks. Moreover, compared with previous protocols, the proposed protocol is lightweight because it relies on symmetric cryptography and it is unaffected by the area covered by the DB.

Association Between Connectivity of Hippocampal Sub-Regions and Auditory Verbal Hallucinations in Schizophrenia.

Background: Hippocampal dysconnectivity has been detected in schizophrenia patients with auditory verbal hallucinations (AVHs). Neuroanatomical evidence has indicated distinct sub-regions in the hippocampus, but which sub-regions within the hippocampus may emerge dysfunction in the brain network, and the relationship between connection strength and the severity of this debilitating disorder have yet to be revealed. Masked independent component analysis (mICA), i.e., ICA restricted to a defined region of interest, can provide insight into observing local functional connectivity in a particular brain region. We aim to map out the sub-regions in the hippocampus with dysconnectivity linked to AVHs in schizophrenia.Methods: In this functional magnetic resonance imaging study of schizophrenia patients with (n = 57) and without (n = 83) AVHs, and 71 healthy controls, we first examined hippocampal connectivity using mICA, and then the correlation between connection metric and clinical severity was generated.Results: As compared with patients without AVHs, mICA showed a group of hyper-connections for the left middle part, as well as another group of hypo-connections for the bilateral antero-lateral and right antero-medial parts in patients with AVHs. Connectivity was linked to the clinical symptoms scores in the sample of patients with AVHs.Conclusion: These findings demonstrate that the left middle part is more densely connected, but the bilateral antero-lateral and right antero-medial parts are more sparsely connected in schizophrenia patients with AVHs. The findings in the present study show proof of precious location in the hippocampus mediating the neural mechanism behind AVHs in schizophrenia.

Blockchains for Supply Chain Management: Architectural Elements and Challenges Towards a Global Scale Deployment

Blockchains are attracting the attention of stakeholders in many industrial domains, including the logistics and supply chain industries. Blockchain technology can effectively contribute in recording every single asset throughout its flow on the supply chain, contribute in tracking orders, receipts, and payments, while track digital assets such as warranties and licenses in a unified and transparent way. The paper provides, through its methodology, a detailed analysis of the blockchain fit in the supply chain industry. It defines the specific elements of blockchain that affect supply chain such as scalability, performance, consensus mechanism, privacy considerations, location proof and cost, and details on the impact that blockchains will have in disrupting the supply chain industry. Discussing the tradeoff between consensus cost, throughput and validation time it proceeds with a suggested high-level architectural approach, and concludes as a result with a discussion on changes needed and challenges faced for an in-vivo deployment of blockchains in the supply chain industry. While the technological features of modern blockchains can effectively facilitate supply chain uses cases, the various challenges that still remain, bring in front of us a wide set of needed changes and further research efforts for achieving a global, production level blockchain for the supply chain industry.

Supporting Spatial-Temporal Provenance Location Proofs for Ad-Hoc Mobile Users

Supporting Spatial-Temporal Provenance Location Proofs for Ad-Hoc Mobile Users

Traffic flow monitoring systems in smart cities: Coverage and distinguishability among vehicles

Traffic flow monitoring systems aim to measure and monitor vehicle trajectories in smart cities. Their critical applications include vehicle theft prevention, vehicle localization, and traffic congestion solution. This paper studies an RoadSide Unit (RSU) placement problem in traffic flow monitoring systems, in order to secure vehicles through location proofs. Given some traffic flows on streets, the objective is to place a minimum number of RSUs to cover and distinguish all traffic flows. A traffic flow is covered and distinguishable, if the set of its passing RSUs is non-empty and unique among all traffic flows. The RSU placement problem is NP-hard, monotonic, and non-submodular. It is a non-trivial extension of the traditional set cover problem that is submodular. Three bounded RSU placement algorithms are proposed with respect to the number of given traffic flows. To further reduce the number of deployed RSUs, this paper extends a credential propagation mechanism via vehicle-to-vehicle communications, which essentially enlarges the coverage of an RSU. Extensive real data-driven experiments demonstrate the efficiency and effectiveness of the proposed algorithms.

Enabling Privacy-Preserving Location Proofs for Mobile Users

Enabling Privacy-Preserving Location Proofs for Mobile Users

Verifiable and Privacy-preserving Check-ins for Geo-social Networks

Enabling efficient and accurate location verification is a desirable technique for the proliferation of many “check-in” based location sharing services. Existing solutions either use modified infrastructures, such as WiFi APs and cellular towers, to issue location proofs for users, which suffer from high infrastructure extension cost, or rely on co-located users to issue location proofs for each other, which are vulnerable to collusion attacks. In this paper, we propose a novel location verification approach that is based on the concept of location tag. When a user requests to check-in at certain venue, both the device of the user and of the venue will submit a location tag, which actually is a collection of environmental signals presented at a certain location and time, to the service provider. Based on the similarity of the two location tags, the service provider can verify whether the user is actually at the location as she claimed. Due to the high time- and space- dependence of environmental signals, it is hard for users to forge location tags. On the other hand, to protect privacy of a user from the location-sharing service, periodically changed pseudonyms are used by users when checking-in at venues, and partially blind signatures are employed by the services to issue check-in confirmation messages. Then users will submit the check-in confirmation messages in a batch manner, using their true Identities. Thus, the location-sharing service knows who has checked-in at which venue, but does not know when the user did. As a result, temporal privacy of user check-ins can be achieved. Thorough analysis and experiments are conducted to demonstrate the feasibility, security and efficiency of the proposed approach.

Location Based Handshake and Private Proximity Test with Location Tags

A location proximity test service allows mobile users to determine whether they are in close proximity to each other, and has found numerous applications in mobile social networks. Unfortunately, existing solutions usually reveal much of users’ private location information during a proximity test. They are also vulnerable to location cheating where an attacker reports false locations to gain an advantage. Moreover, the initial trust establishment among unfamiliar users in large scale mobile social networks has been a challenging task. In this paper, we propose a novel scheme that enables a user to perform (1) a location based handshake that establishes secure communications among strangers, who do not have a pre-shared secret, and (2) a privacy-preserving proximity test without revealing the user’s actual location to the server or other users not within the proximity. The proposed scheme is based on a novel concept, i.e., spatial-temporal location tags, and we put forward a location tag construction method using environmental signals that provides an unforgeable location proof. We use Bloom filters to efficiently represent users’ location tags and vicinity regions. We exploit fuzzy extractor, a lightweight cryptographic primitive, to extract shared secrets between matching location tags. We conduct extensive analysis, simulation, and real experiments to demonstrate the feasibility, security, and efficiency of our scheme.

‘Mobile Ping Data’ – Metadata for Tracking

In this paper Professor Reg Coutts and Hugh Selby explain the current technology and associated data available to assist with monitoring the location and movement of mobile devices. Their paper describes the source of Visiting Location Register (VLR) data and how it can be used to infer ‘trajectory’ of mobile phones and other mobile devices when they are switched on and when there is no call activity and hence no associated Call Charge Records (CCRs). The authors examine the potential of VLR data to provide greater insight into the movement of mobile devices of interest enhances the capabilities of law enforcement to build a case. Index words: Australia, Mobile devices, Telephone, SIM, tracking, records, proof of location

Locate Me: A Privacy Preserving Pseudonym Generation of Location Proof Updates Through Co-Located Devices

Locate Me: A Privacy Preserving Pseudonym Generation of Location Proof Updates Through Co-Located Devices

STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

Location-based services are quickly becoming immensely popular. In addition to services based on users' current location, many potential services rely on users' location history, or their spatial-temporal provenance. Malicious users may lie about their spatial-temporal provenance without a carefully designed security system for users to prove their past locations. In this paper, we present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting. However, it can easily accommodate trusted mobile users and wireless access points. STAMP ensures the integrity and non-transferability of the location proofs and protects users' privacy. A semi-trusted Certification Authority is used to distribute cryptographic keys as well as guard users against collusion by a light-weight entropy-based trust evaluation approach. Our prototype implementation on the Android platform shows that STAMP is low-cost in terms of computational and storage resources. Extensive simulation experiments show that our entropy-based trust model is able to achieve high $(>0.9)$ collusion detection accuracy.

Privacy-Preserving Location Proof for Securing Large-Scale Database-Driven Cognitive Radio Networks

The latest Federal Communications Commission (FCC) ruling has enforced database-driven cognitive radio networks (CRNs), in which all secondary users (SUs) can query a database to obtain spectrum availability information (SAI). Database-driven CRNs are regarded as a promising approach for dynamic and highly efficient spectrum management paradigm for large-scale Internet of Things (IoT). However, as a typical location-based service (LBS), before providing services to the user, there is no verification of the queried location, which is very vulnerable to location spoofing attack. A malicious user can report a fake location to the database and access the channels that may not be available for its location. This will introduce serious interference to the primary users (PUs). In this study, we identify a new kind of attack coined as location cheating attack, which allows an attacker to spoof other users to another location and make them query the database with wrong location, or allows a malicious user to forge location arbitrarily and query the database for services. To thwart this attack, we propose a novel infrastructure-based approach that relies on the existing WiFi or cellular network access points (or AP) to provide privacy-preserving location proof. With the proposed solution, the database can verify the locations without knowing the user’s accurate location. We perform comprehensive experiments to evaluate the performance of the proposed approach. Experimental results show that our approach, besides providing location proofs effectively, can significantly improve the user’s location privacy.

Privacy-preserving distributed location proof generating system

The rapid development of location-based service (LBS) drives one special kind of LBS, in which the service provider verifies user location before providing services. In distributed location proof generating schemes, preventing users from colluding with each other to create fake location proofs and protecting user's location privacy at the same time, are the main technical challenges to bring this kind of LBS into practical. Existing solutions tackle these challenges with low collusion-detecting efficiency and defected collusion-detecting method. We proposed two novel location proof generating schemes, which inversely utilized a secure secret-sharing scheme and a pseudonym scheme to settle these shortcomings. Our proposed solution resists and detects user collusion attacks in a more efficient and correct way. Meanwhile, we achieve a higher level of location privacy than that of previous work. The correctness and efficiency of our proposed solution is testified by intensive security analysis, performance analysis, as well as experiments and simulation results.

WORAL: A Witness Oriented Secure Location Provenance Framework for Mobile Devices

Location-based services allow mobile device users to access various services based on the users’ current physical location information. Path-critical applications, such as supply chain verification, require a chronological ordering of location proofs. It is a significant challenge in distributed and user-centric architectures for users to prove their presence and the path of travel in a privacy-protected and secure manner. So far, proposed schemes for secure location proofs are mostly subject to tampering, not resistant to collusion attacks, do not offer preservation of the provenance, and are not flexible enough for users to prove their provenance of location proofs. In this paper, we present WORAL, a complete ready-to-deploy framework for generating and validating witness oriented asserted location provenance records. The WORAL framework is based on the asserted location proof protocol and the OTIT model for generating secure location provenance on the mobile devices. WORAL allows user-centric, collusion resistant, tamper-evident, privacy protected, verifiable, and provenance preserving location proofs for mobile devices. This paper presents the schematic development, feasibility of usage, comparative advantage over similar protocols, and implementation of WORAL for android device users including a Google Glass-based client for enhanced usability.

VProof: Lightweight Privacy-Preserving Vehicle Location Proofs

Transportation systems relying on vehicles to collect data for services such as road condition monitoring are vulnerable to malicious vehicles injecting large amounts of fake data. A particularly serious type of attack is one in which attackers report fake information about numerous places without actually having been there. In this paper, we present VProof, which is a vehicle location proof scheme that enables a vehicle to prove that its location claims match its historical locations. With VProof, vehicles construct their location proofs by simply extracting relevant contents from the packets received from roadside units. Our scheme is lightweight, since there is no communication required for a prover to obtain a location proof. Our scheme also well preserves users' privacy, as we do not put any information that can be related to a user's ID in a location proof. We have implemented a prototype VProof system and evaluated it with extensive real-world experiments. Our evaluation results show that VProof is able to reliably prove vehicle's locations without leaking any user privacy.