Location Service Provider Research Articles

Efficient and Privacy-Preserving Dynamic Spatial Query Scheme for Ride-Hailing Services

With the prosperity of mobile internet and the pervasiveness of location-aware mobile terminals, online ride-hailing, a high-level location-based service (LBS) which relies on dynamic spatial query, has made our life more convenient. However, the flourish of ride-hailing service still faces many severe challenges since users’ location privacy and service provider's data security. In this paper, we present an efficien t and p r ivacy-preserving dyn a mi c spatial qu e ry scheme (TRACE) for ride-hailing service. With TRACE, users (i.e., consumers and vehicles) can access ride-hailing service without divulging their sensitive location information, meanwhile, the ride-hailing server can achieve the necessary commercial operating information while keeping its sensitive data (i.e., the space division information) confidential. Specifically, with two proposed efficient and secure spatial query algorithms, named FSSQ and ESVQ, all location-related data are encrypted by its owner before being sent out, and are calculated without decryption during the spatial query process. Therefore, consumers, vehicles, and service provider cannot obtain each other's sensitive information. Detailed security analysis shows that TRACE can resist various known security threats. Furthermore, TRACE is implemented in the real environment, and extensive simulation results over smart phones demonstrate that the scheme is highly efficient and can be implemented effectively.

A Dual Privacy Preserving Scheme in Continuous Location-Based Services

With the development of wireless communication and positioning technology, location-based services (LBSs) have been gaining tremendous popularity, due to its ability to greatly facilitate the people’s daily lives. Meanwhile, it also entails the risk of location privacy disclosure. To address this issue, general solutions introduce a single trusted anonymizer between the users and the location service provider (LSP). However, a single anonymizer offers limited privacy guarantees and incurs high communication overhead in continuous LBSs. Once the anonymizer is compromised, it may put the user information in jeopardy. In this paper, we propose a dual privacy preserving (DPP) scheme in continuous LBSs to protect the users’ trajectory and query privacy. Our scheme introduces multiple anonymizers between the users and LSP, and combines with Shamir threshold mechanism, dynamic pseudonym mechanism, and ${K}$ -anonymity technology to improve the users’ trajectory and content privacy in continuous LBSs. An anonymizer alone cannot get the users’ trajectory and query contents, and it thus can be semi-trusted. Our scheme can enhance the users’ privacy and effectively solve the single point of failure in single anonymizer structure. At the same time, the query authentication can guarantee the correctness of the query results. The analysis and simulation results demonstrate that the proposed scheme has the ability to protect users’ trajectory and content privacy effectively, and to reduce the computation and communication overhead of the single anonymizer.

A Method of Location Privacy Protection in Road Network Environment

With the widespread application of location-based services, users 'privacy concerns have become the focus of users' attention. Based on the k-anonymity method and the SpaceTwist algorithm, this paper proposes a method of incremental inquiry user privacy protection. The method preliminarily anonymizes the user's location information and points of interest on the client side, On the anonymous server side, combining the road network environment with the latitude and longitude grid generates the minimum anonymous area of random loop, instead of the user initiating incremental inquiry to the location service provider, Anonymous zones ensure k-anonymity for mobile users and road information to protect user privacy. Security and experimental analysis show that this scheme can improve the effectiveness of user query service while meeting the privacy requirements of users.

A resource-aware approach for authenticating privacy preserving GNN queries

Nowadays many location service providers (LSPs) employ spatial databases outsourced from a third-party data owner (DO) to answer various users’ queries, e.g., group nearest neighbor (GNN) queries that enable a group of users to find a meeting place minimizing their aggregate travel distance. Along with the benefits from LSPs and DO, protection of location privacy and authentication of query results become two major concerns for users while assessing GNN queries. This paper proposes a resource-aware approach that supports effective location privacy preservation and efficient query result authentication with a less storage, communication and computation overhead. Specifically, two centroid-based techniques are investigated to generate a centroid point, which initiates GNN query on behalf of the group members. Then, an authentication algorithm based on Voronoi diagram is proposed for spatial queries. Finally, we demonstrate how our approach is resistant to various attacks, and evaluate its performance by comparing with three competitive approaches. The results show the proposed approach is better and more economical in terms of resource overhead, while considering both privacy preservation and query authentication.

Enhancing privacy through uniform grid and caching in location-based services

With the increasing popularity of location-based services (LBSs), there is a corresponding increase in the potential for location privacy leakage. Existing solutions generally introduce a fully-trusted third party between the users and the location service provider (LSP). However, such an approach offers limited privacy guarantees and incurs high communication overhead. Specifically, once a fully-trusted third party is compromised, user information would likely be exposed. In this paper, we propose a solution designed to enhance location privacy in LBSs. Our scheme is based on the uniform grid, and adopts both order-preserving symmetric encryption (OPSE) andk-anonymity technique. Thus, the anonymizer knows nothing about a user’s real location, and it can only implement simple matching and comparison operations. In our approach, we also employ an entity (hereafter referred to as the converter) to transform the user-defined grid structure into the uniform grid structure. This combined with the caching mechanism, allow us to avoid repeated queries from different users on the same query spatial region and consequently, reduce the overhead of the LBS server. The analysis and simulation results demonstrate that our proposal can effectively preserve a user’s location privacy, with reduced overheads at the anonymizer and the LBS server.

Enhanced Location Privacy Preserving Scheme in Location-Based Services

With the increasing popularity of mobile communication devices loaded with positioning capabilities (e.g., GPS), there is growing demand for enjoying location-based services (LBSs). An important problem in LBSs is the disclosure of a user's real location while interacting with the location service provider (LSP). To address this issue, existing solutions generally introduce a trusted Anonymizer between the users and the LSP. However, the introduction of an Anonymizer actually transfers the security risks from the LSP to the Anonymizer. Once the Anonymizer is compromised, it may put the user information in jeopardy. In this paper, we propose an enhanced-location-privacy-preserving scheme for the LBS environment. Our scheme employs an entity, termed Function Generator, to distribute the spatial transformation parameters periodically, with which the users and the LSP can perform the mutual transformation between a real location and a pseudolocation. Without the transforming parameters, the Anonymizer cannot have any knowledge about a user's real location. The main merits of our scheme include the following: 1) no fully trusted entities are required, and 2) each user can obtain accurate points of interest while preserving location privacy. The efficiency and effectiveness of the proposed scheme are validated by extensive experiments. The experimental results show that the proposed scheme preserves location privacy at low computational and communication cost.

A crowd enabled approach for processing nearest neighbor and range queries in incomplete databases with accuracy guarantee

With the proliferation of mobile devices and wireless technologies, location based services (LBSs) are becoming popular in smart cities. Two important classes of LBSs are Nearest Neighbor (NN) queries and range queries that provide user information about the locations of point of interests (POIs) such as hospitals or restaurants. Answers of these queries are more reliable and satisfiable if they come from trustworthy crowd instead of traditional location service providers (LSPs). We introduce an approach to evaluate NN and range queries with crowdsourced data and computation that eliminates the role of an LSP. In our crowdsourced approach, a user evaluates LBSs in a group. It may happen that group members do not have knowledge of all POIs in a certain area. We present efficient algorithms to evaluate queries with accuracy guarantee in incomplete databases. Experiments show that our approach is scalable and incurs less computational overhead.

Privacy-preserving nearest neighbor queries using geographical features of cellular networks

Although location-based services (LBSes), such as nearest neighbor query, have become popular, privacy remains a challenging issue for users. Many privacy preserving techniques have been proposed, but their complexity, insufficiency, and time consumption make them unattractive to users, who prefer accuracy and quickness. To address this limitation, we introduce a framework to protect user privacy for nearest neighbor queries by utilizing the basic geographical features of cellular networks. In the proposed framework, we provide two layers of spatial anonymity such that the user’s location is not directly provided to a location service provider. Based on the features of the cellular network (e.g., LTE) at the first layer, the user’s location is kept hidden under the cloaking of the base station (eNB) that provides a network connectivity to serve the user (SeNB). At the second layer, we anonymize SeNB in a group of dummy locations neighboring a central eNB (CeNB), all of which have the same query probability. Unlike most existing approaches with faked dummy locations, the proposed framework depends on real locations of eNBs to minimize the likelihood that side information might be exposed to an adversary. Moreover, our model is motivated by the practicality of employing the ubiquity of cellular networks and their geographical features. The simulation results show that the proposed scheme can achieve a decent degree of accuracy (> 98%) while providing strong privacy guarantees.

One-round secure fair meeting location determination based on homomorphic encryption

Determination of optimal meeting location without revealing the locations of participants to the location server is an interesting research problem. A major concern for a location based service is location privacy. However, adding privacy protection to a location service will inevitably introduce computational complexity. To provide location privacy with low computational cost is a challenging task. In this paper, we propose a one-round meeting location determination protocol, where the location service provider makes a decision with a semi-trusted cloud server which works as a computation center and conducts most of computation. The user location privacy is preserved against the outside and internal attackers including the computation center, the meeting location determination server and participants. In order to study the performance of the protocol, we test its computational efficiency on smartphones. The simulation results and the performance comparison of our protocol with another protocol of the same functionalities demonstrate that our solution is more efficient and practical.

Collaborative trajectory privacy preserving scheme in location-based services

Location-based services (LBSs) have been gaining considerable popularity and are becoming the fastest growing activity-related services that people use in their daily life. While users benefit from LBSs, the collection and analysis of participators’ location data and trajectory information may jeopardize their privacy. Existing proposals focus mostly on snapshot queries. However, privacy preservation in continuous LBSs is more challenging than in snapshot queries because adversaries could use the spatial and temporal correlations on the user trajectory to infer the user’s private information. In this paper, we propose the collaborative trajectory privacy preserving (CTPP) scheme for continuous queries, in which trajectory privacy is guaranteed by caching-aware collaboration between users, without the need for any fully trusted entities. The main idea of our scheme is to obfuscate the actual trajectory of a user by issuing fake queries to confuse the LBS adversary. We first present a multi-hop caching-aware cloaking algorithm to collect valuable information from multi-hop peers based on collaborative caching. Then, we describe a collaborative privacy preserving querying algorithm that issues a fake query to confuse the location service provider (LSP). Extensive experimental results verify the effectiveness and efficiency of our scheme in terms of processing time and communication cost.

A Framework for Simultaneous Message Broadcasting Using CDMA-Based Visible Light Communications

Internet of Things applications are fast growing recently. One of the things that has a lot of potential is the lighting equipment since it is widely used in our daily life. Recently, the technology of visible light communication (VLC) has been widely discussed. VLC has several advantages, such as freedom of license, line-of-sight security, and less health concern compared with radio-based systems. In addition, the rapid progress of light emitting diode (LED) technology by solid-state lighting allows VLC to be easily deployed and integrated with the existing lighting infrastructure at low costs. However, VLC, when integrated with lighting infrastructure, is usually for one-way communication and is highly sensitive to external interfering light. Thus, transmitting or broadcasting multiple messages simultaneously over a visible light channel without any preprocessing may result in serious collisions. In this paper, we propose a framework to tackle these problems by optical code division multiple access (CDMA) for VLC. With our approach, a VLC receiver can enter an environment without any prior configuration and can be designed with simple hardware. Even a mobile device with a high-resolution photodiode sensor can be used as a receiver. We demonstrate an application of indoor positioning by querying the location service provider on the Internet with the IDs decoded from the received light signals. The prototyping results reveal some communication properties of CDMA-based VLC and its potential for indoor positioning applications.

Authentication User’s Privacy: An Integrating Location Privacy Protection Algorithm for Secure Moving Objects in Location Based Services

Location based services (LBSs) are gaining importance due to the advancement in mobile networks and positioning technologies. The proliferation of location-based services in recent years has highlighted the need to consider location privacy. This has led to the development of methods enhancing location privacy, and to the investigation of reasons for sharing location information. While computational attacks on location privacy and their prevention have attracted a lot of research, attacks based on humans strategies and tactics have mostly been considered implicitly. Nevertheless, in querying LBSs, a user send its exact locations to their location service providers but in the process, location information of the users are misused either purposefully or otherwise by service providers creating privacy issues for users. It has therefore become important that mechanisms necessary to protect the privacy of users are adopted when querying location based services. It's on this premise that we introduced a novel query privacy algorithm called the authentication speed dynamic transportation mode cloaking algorithm for continuous query LBSs that considers users' similarity in speed, direction and travelling with the same transport mode for cloaking for anonymization. Experimental evaluation of the algorithm on a real world map shows that our model ensures total privacy for users, enhanced privacy guarantee, improves quality of service significantly and achieved an excellent performance measure also we compare our method with existing privacy protection methods such as V-DCA, DSDCA, AVD-DCA,D-TC and GCA.

A Comparative Analysis of Number Portability Routing Schemes

To reap the benefits of liberalized telecom market, the implementation of number portability (NP) is utmost important. NP allows end user to retain their telephone number in case of change of geographical location or service type or service provider. This paper describes the various number portability routing schemes namely, All Call Query, Query on Release, Call Dropback and Onward routing. The comparative analysis between these routing schemes on various parameters is presented here. The issues pertaining to NP have also been described.

Sketching and validating the location-based services (LBS) regulatory framework in Australia

Location-based services (LBS) are defined as those applications that combine the location of a mobile device associated with a given entity (individual or object) together with contextual information to offer a value-added service. LBS solutions are being deployed globally, and in some markets like Australia, without appropriate regulatory provisions in place. Recent debates in Australia have addressed the need to bridge the gap between technological developments and legal/regulatory provisions. This requires an assessment of the regulatory environment within a given social context such as Australia. The core components of such an investigation include: (a) composing a conceptual framework for analysing regulation of technologies such as LBS, one that is sensitive to public policy themes and challenges, and (b) applying this conceptual framework to the Australian setting in order to sketch and define the components of the present framework, and identify areas for improvement through a process of validation. This paper addresses these aims, demonstrating how the current regulatory framework in Australia is bound by legislation with respect to privacy, telecommunications, surveillance, and national security (that is, anti-terrorism), in addition to a set of industry guidelines for location-service providers (LSPs). The existing Australian framework, however, is lacking in its coverage and treatment of LBS and location data, and does not adequately address the themes and challenges in the defined conceptual framework.

A Model of LBS Privacy Protection Based on Collaboration

How to protect users privacy effectively while providing location based service (LBS) is a very important study of the mobile Internet. Where location k-anonymity algorithm is the most commonly used algorithm at present. However the algorithm also has some disadvantages. Therefore, this paper presents a model of LBS privacy protection based on collaboration. It divides a location-based query into two parts and sends to two entities separately. One is the location cloaking server (LCS) which calculates k-anonymous locations, and the other is location service provider (LSP) which implements the query. Except the user none of the servers could have the complete query information. By this way it protects the users privacy very well. The algorithm partly solved the problems existing in the traditional k-anonymity algorithm, and the algorithms performance was significantly increased.

Balancing trajectory privacy and data utility using a personalized anonymization model

With the widespread use of location-based services (LBS), the number of trajectories gathered by location service providers is dynamically growing. On the one hand, mining and analyzing these spatiotemporal trajectories can help to work out a mobile-related strategic planning; on the other hand, knowledge of each trajectory can be used by adversaries to identify the user's sensitive information and lead to an unpredictable harm. The concept of trajectory k-anonymity extends from location k-anonymity that has been widely used to address this issue. The main challenge of trajectory k-anonymity is the selection of a trajectory k-anonymity set. However, existing anonymity methods ignore the trajectory similarity and direction, assuming that it has little impact on privacy. Thus, it cannot provide a preferable trajectory k-anonymity set. In this paper, we propose to use trajectory angle to evaluate trajectory similarity and direction, and construct an anonymity region on the basis of trajectory distance. Considering the various preference settings on the proportion of trajectory privacy and data utility in different scenarios, we propose a personalized anonymization model to select the trajectory k-anonymity set. Experiment results prove that our method can provide an effective trajectory k-anonymity set under various proportions of trajectory privacy and data utility requirements, while the efficiency just reduces a little.

PShare: Ensuring location privacy in non-trusted systems through multi-secret sharing

Location-based applications such as Facebook Places, Foursquare, or Loopt typically use location services to manage mobile object positions. However, exposing precise user positions raises user privacy concerns, especially if location service providers are not fully trusted. To enable the secure management of private user positions in non-trusted systems, we present two novel position sharing approaches based on the concept of multi-secret sharing. We improve existing geometric position sharing approaches by Dürr et al. [2] and Skvortsov et al. [3] by considering continuous position updates and by increasing the robustness against various attacks. Furthermore, we present the first position sharing approach for symbolic location models.