With the evolution of location-based services(LBS),a new type of LBS has already gain a lot of attention and implementation,we name this kind of LBS as the Device-Dependent LBS(DLBS).In DLBS,the service provider(SP)wi...With the evolution of location-based services(LBS),a new type of LBS has already gain a lot of attention and implementation,we name this kind of LBS as the Device-Dependent LBS(DLBS).In DLBS,the service provider(SP)will not only send the information according to the user’s location,more significant,he also provides a service device which will be carried by the user.DLBS has been successfully practised in some of the large cities around the world,for example,the shared bicycle in Beijing and London.In this paper,we,for the first time,blow the whistle of the new location privacy challenges caused by DLBS,since the service device is enabled to perform the localization without the permission of the user.To conquer these threats,we design a service architecture along with a credit system between DLBS provider and the user.The credit system tie together the DLBS device usability with the curious behaviour upon user’s location privacy,DLBS provider has to sacrifice their revenue in order to gain extra location information of their device.We make the simulation of our proposed scheme and the result convince its effectiveness.展开更多
With the rapid development of the Internet of Things(IoT),Location-Based Services(LBS)are becoming more and more popular.However,for the users being served,how to protect their location privacy has become a growing co...With the rapid development of the Internet of Things(IoT),Location-Based Services(LBS)are becoming more and more popular.However,for the users being served,how to protect their location privacy has become a growing concern.This has led to great difficulty in establishing trust between the users and the service providers,hindering the development of LBS for more comprehensive functions.In this paper,we first establish a strong identity verification mechanism to ensure the authentication security of the system and then design a new location privacy protection mechanism based on the privacy proximity test problem.This mechanism not only guarantees the confidentiality of the user s information during the subsequent information interaction and dynamic data transmission,but also meets the service provider's requirements for related data.展开更多
Recently, location-based routings in wireless sensor networks (WSNs) are attracting a lot of interest in the research community, especially because of its scalability. In location-based routing, the network size is sc...Recently, location-based routings in wireless sensor networks (WSNs) are attracting a lot of interest in the research community, especially because of its scalability. In location-based routing, the network size is scalable without increasing the signalling overhead as routing decisions are inherently localized. Here, each node is aware of its position in the network through some positioning device like GPS and uses this information in the routing mechanism. In this paper, we first discuss the basics of WSNs including the architecture of the network, energy consumption for the components of a typical sensor node, and draw a detailed picture of classification of location-based routing protocols. Then, we present a systematic and comprehensive taxonomy of location-based routing protocols, mostly for sensor networks. All the schemes are subsequently discussed in depth. Finally, we conclude the paper with some insights on potential research directions for location-based routing in WSNs.展开更多
Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communica...Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.展开更多
Mobile professionals need to be assisted with suitable mobile GeoBI (Geospatial Business Intelligence) systems, which are able to capture, organize and structure the user’s reality into a relevant context model and r...Mobile professionals need to be assisted with suitable mobile GeoBI (Geospatial Business Intelligence) systems, which are able to capture, organize and structure the user’s reality into a relevant context model and reason on it. GeoBI context modelling and reasoning are still research issues since there is not yet either a model or a relevant taxonomy regarding GeoBI contextual information. To fill this gap, this paper proposes an extended and detailed OWL-based mobile GeoBI context ontology to provide context-aware applications and users with relevant contextual information and context-based reasoning capabilities. Context quality issues are handled an implementation architecture which is provided.展开更多
In Delay Tolerant Networks(DTNs),the offiine users can,through the encountering nodes,use the specific peer-to-peer message routing approach to deliver messages to the destination.Thus,it solves the problem that users...In Delay Tolerant Networks(DTNs),the offiine users can,through the encountering nodes,use the specific peer-to-peer message routing approach to deliver messages to the destination.Thus,it solves the problem that users have the demands to deliver messages while they are temporarily not able to connect to the Internet.Therefore,by the characteristics of DTNs,people who are not online can still query some location based information,with the help of users using the same service in the nearby area.In this paper,we proposed a location-based content search approach.Based on the concept of three-tier area and hybrid node types,we presented four strategies to solve the query problem,namely,Data Replication,Query Replication,Data Reply,and Data Synchronization strategies.Especially we proposed a Message Queue Selection algorithm for message transferring.The priority concept is set associated with every message such that the most"important"one could be sent first.In this way,it can increase the query success ratio and reduce the query delay time.Finally,we evaluated our approach,and compared with other routing schemes.The simulation results showed that our proposed approach had better query efficiency and shorter delay.展开更多
Routing algorithms based on geographical location is an important research subject in the Wireless Sensor Network(WSN).They use location information to guide routing discovery and maintenance as well as packet forward...Routing algorithms based on geographical location is an important research subject in the Wireless Sensor Network(WSN).They use location information to guide routing discovery and maintenance as well as packet forwarding,thus enabling the best routing to be selected,reducing energy consumption and optimizing the whole network.Through three aspects involving the flooding restriction scheme,the virtual area partition scheme and the best routing choice scheme,the importance of location information is seen in the routing algorithm.展开更多
<div style="text-align:justify;"> In the era of information and communication technology (ICT) and big data, the map gradually shows a new qualitative feature of “spatiotemporal ubiquitous” due to th...<div style="text-align:justify;"> In the era of information and communication technology (ICT) and big data, the map gradually shows a new qualitative feature of “spatiotemporal ubiquitous” due to the extension of its object space and the geographic information it contains, which brings new challenges to map information organization. This paper analyzes the concept and information characteristics of the ubiquitous map. Based on that, it proposes a ubiquitous map information organization model oriented to location-based aggregation. This new model includes three parts as “ubiquitous map instance”, “location-based aggregation mode” and “map scene”. This paper focuses on the “map scene” part which is the core of the model and contains two mutually mapped aspects as “content scene” and “representation scene”. And both aspects are divided into three levels as “features” ←→ “elements” ←→ “scenes” according to ubiquitous map information characteristics and location-based aggregation mode. With cases of map decomposition, the application of the model is explained to illustrate its effectiveness. The model is expected to provide powerful data organization and management capabilities for ubiquitous map production and use. </div>展开更多
Casper Cloak is a privacy protection method based on K-anonymity algorithm. To be anonymous, Casper Cloak needs to search regional sibling and parent node, which requires a complex process and huge expenditure. In add...Casper Cloak is a privacy protection method based on K-anonymity algorithm. To be anonymous, Casper Cloak needs to search regional sibling and parent node, which requires a complex process and huge expenditure. In addition,the anonymous area has space redundancy and it is not accurate enough to achieve high Location-Based Services (LBS) quality. To address these problems,this paper proposes an improved privacy protection method-NCC, based on the Casper Cloak. To reduce the unnecessary search, NCC introduced the concept of the first sibling node. NCC also improves the LBS quality by considering the characteristics of user mobility. Moreover, the improved method,NCC, which is incorporated with a redundancy optimization processing strategy,realizing more precise in the anonymous area and accurately guaranteeing the related degree of privacy. Adopting NCC verification experiments reflects varied advantages as bellow: (1) By reducing 80% searching time, NCC highly improved searching process. (2) The anonymous area produced in NCC not only meet users' anonymous demands, but the direction of the mobility which improves 4 times accuracy of services in comparison with Casper mode.(3) According to optimization strategy, NCC can reach minimum anonymous area index, increasing the rates of anonymous optimization in original algorithm.展开更多
Location-based social network （LBSN） is at the forefront of emerging trends in social network services （SNS） since the users in LBSN are allowed to ＂check-in＂ the places （locations） when they visit them. The a...Location-based social network （LBSN） is at the forefront of emerging trends in social network services （SNS） since the users in LBSN are allowed to ＂check-in＂ the places （locations） when they visit them. The accurate geographi- cal and temporal information of these check-in actions are provided by the end-user GPS-enabled mobile devices, and recorded by the LBSN system. In this paper, we analyze and mine a big LBSN data, Gowalla, collected by us. First, we investigate the relationship between the spatio-temporal co- occurrences and social ties, and the results show that the co- occurrences are strongly correlative with the social ties. Sec- ond, we present a study of predicting two users whether or not they will meet （co-occur） at a place in a given future time, by exploring their check-in habits. In particular, we first intro- duce two new concepts, bag-of-location and bag-of-time-lag, to characterize user＇s check-in habits. Based on such bag rep- resentations, we define a similarity metric called habits sim- ilarity to measure the similarity between two users＇ check-in habits. Then we propose a machine !earning formula for pre- dicting co-occurrence based on the social ties and habits sim- ilarities. Finally, we conduct extensive experiments on our dataset, and the results demonstrate the effectiveness of the proposed method.展开更多
Location privacy has been a serious concern for mobile users who use location-based services provided by third-party providers via mobile networks. Recently, there have been tremendous efforts on developing new anonym...Location privacy has been a serious concern for mobile users who use location-based services provided by third-party providers via mobile networks. Recently, there have been tremendous efforts on developing new anonymity or obfuscation techniques to protect location privacy of mobile users. Though effective in certain scenarios, these existing techniques usually assume that a user has a constant privacy requirement along spatial and/or temporal dimensions, which may be not true in real-life scenarios. In this paper, we introduce a new location privacy problem： Location-aware Location Privacy Protection （L2P2） problem, where users can define dynamic and diverse privacy requirements for different locations. The goal of the L2P2 problem is to find the smallest cloaking area for each location request so that diverse privacy requirements over spatial and/or temporal dimensions are satisfied for each user. In this paper, we formalize two versions of the L2P2 problem, and propose several efficient heuristics to provide such location-aware location privacy protection for mobile users. Through extensive simulations over large synthetic and real-life datasets, we confirm the effectiveness and efficiency of the proposed L2P2 algorithms.展开更多
The widespread use of Location-Based Services （LBSs）, which allows untrusted service providers to collect large quantities of information regarding users＇ locations, has raised serious privacy concerns. In response...The widespread use of Location-Based Services （LBSs）, which allows untrusted service providers to collect large quantities of information regarding users＇ locations, has raised serious privacy concerns. In response to these issues, a variety of LBS Privacy Protection Mechanisms （LPPMs） have been recently proposed. However, evaluating these LPPMs remains problematic because of the absence of a generic adversarial model for most existing privacy metrics. In particular, the relationships between these metrics have not been examined in depth under a common adversarial model, leading to a possible selection of the inappropriate metric, which runs the risk of wrongly evaluating LPPMs. In this paper, we address these issues by proposing a privacy quantification model, which is based on Bayes conditional privacy, to specify a general adversarial model. This model employs a general definition of conditional privacy regarding the adversary＇s estimation error to compare the different LBS privacy metrics. Moreover, we present a theoretical analysis for specifying how to connect our metric with other popular LBS privacy metrics. We show that our privacy quantification model permits interpretation and comparison of various popular LBS privacy metrics under a common perspective. Our results contribute to a better understanding of how privacy properties can be measured, as well as to the better selection of the most appropriate metric for any given LBS application.展开更多
This paper presents various limitations of the current remote sensing data distribution models and proposes a new concept called the location-based instant satellite image service for a new generation of remote sensin...This paper presents various limitations of the current remote sensing data distribution models and proposes a new concept called the location-based instant satellite image service for a new generation of remote sensing image distribution system.The essential feature of the service is that customers can subscribe to data based on the location of interest and satellite image data received by antenna will be distributed to customer’s terminal devices instantly after imaging over the subscribed area.The workflow,architecture,and key technologies of the new generation data distribution system are described.The system is composed of four parts:data comprehensive processing component,data management component,product distribution component,and data display component.Based on this,a prototype system is developed,which demonstrates the promising service model with great potential for increased usage in many applications.展开更多
The wide spread of location-based social networks brings about a huge volume of user check-in data, whichfacilitates the recommendation of points of interest （POIs）. Recent advances on distributed representation she...The wide spread of location-based social networks brings about a huge volume of user check-in data, whichfacilitates the recommendation of points of interest （POIs）. Recent advances on distributed representation shed light onlearning low dimensional dense vectors to alleviate the data sparsity problem. Current studies on representation learningfor POI recommendation embed both users and POIs in a common latent space, and users＇ preference is inferred basedon the distance/similarity between a user and a POI. Such an approach is not in accordance with the semantics of usersand POIs as they are inherently different objects. In this paper, we present a novel translation-based, time and locationaware （TransTL） representation, which models the spatial and temporal information as a relationship connecting users andPOIs. Our model generalizes the recent advances in knowledge graph embedding. The basic idea is that the embedding ofa 〈time, location〉 pair corresponds to a translation from embeddings of users to POIs. Since the POI embedding shouldbe close to the user embedding plus the relationship vector, the recommendation can be performed by selecting the top-kPOIs similar to the translated POI, which are all of the same type of objects. We conduct extensive experiments on tworeal-world data.sets. The results demonstrate that our TransTL model achieves the state-of-the-art performance. It is alsomuch more robust to data sparsity than the baselines.展开更多
Since smartphones embedded with positioning systems and digital maps are widely used,location-based services(LBSs)are rapidly growing in popularity and providing unprecedented convenience in people’s daily lives;howe...Since smartphones embedded with positioning systems and digital maps are widely used,location-based services(LBSs)are rapidly growing in popularity and providing unprecedented convenience in people’s daily lives;however,they also cause great concern about privacy leakage.In particular,location queries can be used to infer users’sensitive private information,such as home addresses,places of work and appointment locations.Hence,many schemes providing query anonymity have been proposed,but they typically ignore the fact that an adversary can infer real locations from the correlations between consecutive locations in a continuous LBS.To address this challenge,a novel dual privacy-preserving scheme(DPPS)is proposed that includes two privacy protection mechanisms.First,to prevent privacy disclosure caused by correlations between locations,a correlation model is proposed based on a hidden Markov model(HMM)to simulate users’mobility and the adversary’s prediction probability.Second,to provide query probability anonymity of each single location,an advanced k-anonymity algorithm is proposed to construct cloaking regions,in which realistic and indistinguishable dummy locations are generated.To validate the effectiveness and efficiency of DPPS,theoretical analysis and experimental verification are further performed on a real-life dataset published by Microsoft,i.e.,GeoLife dataset.展开更多
The authors compare key elements of the emerging field of Indoor Location-Based Services(Indoor LBS)to those currently found in spatial data infrastructure(SDI)programs.After a brief review of SDIs and Location-Based ...The authors compare key elements of the emerging field of Indoor Location-Based Services(Indoor LBS)to those currently found in spatial data infrastructure(SDI)programs.After a brief review of SDIs and Location-Based Services,the corresponding drivers,characteristics and emerging issues within the field of Indoor LBS are introduced and discussed.A comparative framework relates the two in terms of the criteria‘People’,‘Data’,‘Technologies’,‘Standards’and‘Policies/Institutional Arrangements’.After highlighting key similarities and differences,the authors suggested three areas–definition of common framework datasets in Indoor LBS,more effective use of volunteered geographic information by SDI programs and development of appropriate privacy policies by both communities–that may benefit from sharing‘lessons learned’.展开更多
A novel testing framework for location based services is introduced. In particular, the paper showcases a novel architecture for such a framework. The implementation of the framework illustrates both the functionality...A novel testing framework for location based services is introduced. In particular, the paper showcases a novel architecture for such a framework. The implementation of the framework illustrates both the functionality and the feasibility of the framework proposed and the utility of the architecture. The new framework is evaluated through comparison to several other methodologies currently available for the testing of location-based applications. A case study is presented in which the testing framework was applied to a typical mobile service tracking system. It is concluded that the proposed testing framework achieves the best coverage of the entire location based service testing problem of the currently available methodologies; being equipped to test the widest array of application attributes and allowing for the automation of testing activities.展开更多
The rising prosperity of Location-based Social Networks(LBSNs)witnessed an explosion in the availability of geo-tagged social media data,which enables tremendous location-aware online services,especially next point of...The rising prosperity of Location-based Social Networks(LBSNs)witnessed an explosion in the availability of geo-tagged social media data,which enables tremendous location-aware online services,especially next point of interest(POI)recommendation.However,previous next POI recommendation studies usually adopt fix-length time windows for user check-in sequence modeling,leading to a limited capacity in capturing fine-grained user temporal preferences that easily change over time.Besides,existing methods often directly leverage multi-modal contexts as auxiliary to alleviate the data sparsity issue,which fails to fully exploit the sequential patterns of contextual information for inferring user interest drift.To address the above challenges,we propose a novel framework named iTourSPOT which extends traditional collaborative filtering methods with a context-aware POI embedding architecture.For enhancing temporal interests modeling capacity,we associate the context feature extraction with varying-length sessions and incorporate check-in frequencies of POIs as prior knowledge to instruct the session representation learning of our model.Moreover,a collaborative sequence transduction model is designed for joint context sequence modeling and session-based POI recommendation.Experimental results on a real-world geo-tagged photo dataset clearly demonstrate the effectiveness of the proposed framework when compared with state-of-the-art baseline methods,especially in both sparse and cold-start scenarios.展开更多
Ubiquitous information exchange is achieved among connected vehicles through the increasingly smart environment.The concept of conventional vehicular ad hoc network is gradually transformed into the Internet of vehicl...Ubiquitous information exchange is achieved among connected vehicles through the increasingly smart environment.The concept of conventional vehicular ad hoc network is gradually transformed into the Internet of vehicles(IoV).Meanwhile,more and more locationbased services(LBSs)are created to provide convenience for drivers.However,the frequently updated location information sent to the LBS server also puts user location privacy at risk.Thus,preserve user location privacy while allowing vehicles to have high-quality LBSs is a critical issue.Many solutions have been proposed in the literature to preserve location privacy.However,most of them cannot provide real-time LBS with accurate location updates.In this paper,we propose a novel location privacy-preserving scheme,which allows vehicles to send accurate real-time location information to the LBS server while preventing being tracked by attackers.In the proposed scheme,a vehicle utilizes the location information of selected shadow vehicles,whose route diverge from the requester,to generate multiple virtual trajectories to the LBS server so as to mislead attackers.Simulation results show that our proposed scheme achieves a high privacy-preserving level and outperforms other state-of-the-art schemes in terms of location entropy and tracking success ratio.展开更多
Many location-based services need to query objects existing in a specific space,such as location-based tourism resource recommendation.Both a large number of spatial objects and the real-time object access requirement...Many location-based services need to query objects existing in a specific space,such as location-based tourism resource recommendation.Both a large number of spatial objects and the real-time object access requirements of location-based services pose a big challenge for spatial object storage and query management.In this paper,we propose HGeoHashBase,an improved storage model by integrating GeoHash with key-value structure,to organize spatial objects for efficient range queries.GeoHash is responsible for spatial encoding and key-value structure as underlying data storage.Both the similarity of the encodings for objects in the close geographical locations and the multi-version data mechanism are blended into the proposed model well.Considering the tradeoff between encoding precision and query performance,a theoretical proof is presented.Extensive experiments are designed and conducted,whose results show that the proposed model can gain significant performance improvement.展开更多
基金This work was supported by National Natural Science Foundation of China(Grant Nos.61871140,61702223,61702220,61572153,61723022,61601146)and the National Key research and Development Plan(Grant No.2018YFB0803504,2017YFB0803300).
文摘With the evolution of location-based services(LBS),a new type of LBS has already gain a lot of attention and implementation,we name this kind of LBS as the Device-Dependent LBS(DLBS).In DLBS,the service provider(SP)will not only send the information according to the user’s location,more significant,he also provides a service device which will be carried by the user.DLBS has been successfully practised in some of the large cities around the world,for example,the shared bicycle in Beijing and London.In this paper,we,for the first time,blow the whistle of the new location privacy challenges caused by DLBS,since the service device is enabled to perform the localization without the permission of the user.To conquer these threats,we design a service architecture along with a credit system between DLBS provider and the user.The credit system tie together the DLBS device usability with the curious behaviour upon user’s location privacy,DLBS provider has to sacrifice their revenue in order to gain extra location information of their device.We make the simulation of our proposed scheme and the result convince its effectiveness.
基金This work has been partly supported by the National Natural Science Foundation of China under Grant No.61702212the Fundamental Research Funds for the Central Universities under Grand NO.CCNU19TS017.
文摘With the rapid development of the Internet of Things(IoT),Location-Based Services(LBS)are becoming more and more popular.However,for the users being served,how to protect their location privacy has become a growing concern.This has led to great difficulty in establishing trust between the users and the service providers,hindering the development of LBS for more comprehensive functions.In this paper,we first establish a strong identity verification mechanism to ensure the authentication security of the system and then design a new location privacy protection mechanism based on the privacy proximity test problem.This mechanism not only guarantees the confidentiality of the user s information during the subsequent information interaction and dynamic data transmission,but also meets the service provider's requirements for related data.
文摘Recently, location-based routings in wireless sensor networks (WSNs) are attracting a lot of interest in the research community, especially because of its scalability. In location-based routing, the network size is scalable without increasing the signalling overhead as routing decisions are inherently localized. Here, each node is aware of its position in the network through some positioning device like GPS and uses this information in the routing mechanism. In this paper, we first discuss the basics of WSNs including the architecture of the network, energy consumption for the components of a typical sensor node, and draw a detailed picture of classification of location-based routing protocols. Then, we present a systematic and comprehensive taxonomy of location-based routing protocols, mostly for sensor networks. All the schemes are subsequently discussed in depth. Finally, we conclude the paper with some insights on potential research directions for location-based routing in WSNs.
基金MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)
文摘Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.
文摘Mobile professionals need to be assisted with suitable mobile GeoBI (Geospatial Business Intelligence) systems, which are able to capture, organize and structure the user’s reality into a relevant context model and reason on it. GeoBI context modelling and reasoning are still research issues since there is not yet either a model or a relevant taxonomy regarding GeoBI contextual information. To fill this gap, this paper proposes an extended and detailed OWL-based mobile GeoBI context ontology to provide context-aware applications and users with relevant contextual information and context-based reasoning capabilities. Context quality issues are handled an implementation architecture which is provided.
文摘In Delay Tolerant Networks(DTNs),the offiine users can,through the encountering nodes,use the specific peer-to-peer message routing approach to deliver messages to the destination.Thus,it solves the problem that users have the demands to deliver messages while they are temporarily not able to connect to the Internet.Therefore,by the characteristics of DTNs,people who are not online can still query some location based information,with the help of users using the same service in the nearby area.In this paper,we proposed a location-based content search approach.Based on the concept of three-tier area and hybrid node types,we presented four strategies to solve the query problem,namely,Data Replication,Query Replication,Data Reply,and Data Synchronization strategies.Especially we proposed a Message Queue Selection algorithm for message transferring.The priority concept is set associated with every message such that the most"important"one could be sent first.In this way,it can increase the query success ratio and reduce the query delay time.Finally,we evaluated our approach,and compared with other routing schemes.The simulation results showed that our proposed approach had better query efficiency and shorter delay.
文摘Routing algorithms based on geographical location is an important research subject in the Wireless Sensor Network(WSN).They use location information to guide routing discovery and maintenance as well as packet forwarding,thus enabling the best routing to be selected,reducing energy consumption and optimizing the whole network.Through three aspects involving the flooding restriction scheme,the virtual area partition scheme and the best routing choice scheme,the importance of location information is seen in the routing algorithm.
文摘<div style="text-align:justify;"> In the era of information and communication technology (ICT) and big data, the map gradually shows a new qualitative feature of “spatiotemporal ubiquitous” due to the extension of its object space and the geographic information it contains, which brings new challenges to map information organization. This paper analyzes the concept and information characteristics of the ubiquitous map. Based on that, it proposes a ubiquitous map information organization model oriented to location-based aggregation. This new model includes three parts as “ubiquitous map instance”, “location-based aggregation mode” and “map scene”. This paper focuses on the “map scene” part which is the core of the model and contains two mutually mapped aspects as “content scene” and “representation scene”. And both aspects are divided into three levels as “features” ←→ “elements” ←→ “scenes” according to ubiquitous map information characteristics and location-based aggregation mode. With cases of map decomposition, the application of the model is explained to illustrate its effectiveness. The model is expected to provide powerful data organization and management capabilities for ubiquitous map production and use. </div>
文摘Casper Cloak is a privacy protection method based on K-anonymity algorithm. To be anonymous, Casper Cloak needs to search regional sibling and parent node, which requires a complex process and huge expenditure. In addition,the anonymous area has space redundancy and it is not accurate enough to achieve high Location-Based Services (LBS) quality. To address these problems,this paper proposes an improved privacy protection method-NCC, based on the Casper Cloak. To reduce the unnecessary search, NCC introduced the concept of the first sibling node. NCC also improves the LBS quality by considering the characteristics of user mobility. Moreover, the improved method,NCC, which is incorporated with a redundancy optimization processing strategy,realizing more precise in the anonymous area and accurately guaranteeing the related degree of privacy. Adopting NCC verification experiments reflects varied advantages as bellow: (1) By reducing 80% searching time, NCC highly improved searching process. (2) The anonymous area produced in NCC not only meet users' anonymous demands, but the direction of the mobility which improves 4 times accuracy of services in comparison with Casper mode.(3) According to optimization strategy, NCC can reach minimum anonymous area index, increasing the rates of anonymous optimization in original algorithm.
文摘Location-based social network （LBSN） is at the forefront of emerging trends in social network services （SNS） since the users in LBSN are allowed to ＂check-in＂ the places （locations） when they visit them. The accurate geographi- cal and temporal information of these check-in actions are provided by the end-user GPS-enabled mobile devices, and recorded by the LBSN system. In this paper, we analyze and mine a big LBSN data, Gowalla, collected by us. First, we investigate the relationship between the spatio-temporal co- occurrences and social ties, and the results show that the co- occurrences are strongly correlative with the social ties. Sec- ond, we present a study of predicting two users whether or not they will meet （co-occur） at a place in a given future time, by exploring their check-in habits. In particular, we first intro- duce two new concepts, bag-of-location and bag-of-time-lag, to characterize user＇s check-in habits. Based on such bag rep- resentations, we define a similarity metric called habits sim- ilarity to measure the similarity between two users＇ check-in habits. Then we propose a machine !earning formula for pre- dicting co-occurrence based on the social ties and habits sim- ilarities. Finally, we conduct extensive experiments on our dataset, and the results demonstrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China (Nos.61370192,61432015,61428203,and 61572347)the US National Science Foundation (Nos.CNS-1319915 and CNS-1343355)
文摘Location privacy has been a serious concern for mobile users who use location-based services provided by third-party providers via mobile networks. Recently, there have been tremendous efforts on developing new anonymity or obfuscation techniques to protect location privacy of mobile users. Though effective in certain scenarios, these existing techniques usually assume that a user has a constant privacy requirement along spatial and/or temporal dimensions, which may be not true in real-life scenarios. In this paper, we introduce a new location privacy problem： Location-aware Location Privacy Protection （L2P2） problem, where users can define dynamic and diverse privacy requirements for different locations. The goal of the L2P2 problem is to find the smallest cloaking area for each location request so that diverse privacy requirements over spatial and/or temporal dimensions are satisfied for each user. In this paper, we formalize two versions of the L2P2 problem, and propose several efficient heuristics to provide such location-aware location privacy protection for mobile users. Through extensive simulations over large synthetic and real-life datasets, we confirm the effectiveness and efficiency of the proposed L2P2 algorithms.
基金supported in part by the National Science and Technology Major Project (No. 2012ZX03002001004)the National Natural Science Foundation of China (Nos. 61172090, 61163009, and 61163010)+1 种基金the PhD Programs Foundation of Ministry of Education of China (No. 20120201110013)the Scientific and Technological Project in Shaanxi Province (Nos. 2012K06-30 and 2014JQ8322)
文摘The widespread use of Location-Based Services （LBSs）, which allows untrusted service providers to collect large quantities of information regarding users＇ locations, has raised serious privacy concerns. In response to these issues, a variety of LBS Privacy Protection Mechanisms （LPPMs） have been recently proposed. However, evaluating these LPPMs remains problematic because of the absence of a generic adversarial model for most existing privacy metrics. In particular, the relationships between these metrics have not been examined in depth under a common adversarial model, leading to a possible selection of the inappropriate metric, which runs the risk of wrongly evaluating LPPMs. In this paper, we address these issues by proposing a privacy quantification model, which is based on Bayes conditional privacy, to specify a general adversarial model. This model employs a general definition of conditional privacy regarding the adversary＇s estimation error to compare the different LBS privacy metrics. Moreover, we present a theoretical analysis for specifying how to connect our metric with other popular LBS privacy metrics. We show that our privacy quantification model permits interpretation and comparison of various popular LBS privacy metrics under a common perspective. Our results contribute to a better understanding of how privacy properties can be measured, as well as to the better selection of the most appropriate metric for any given LBS application.
文摘This paper presents various limitations of the current remote sensing data distribution models and proposes a new concept called the location-based instant satellite image service for a new generation of remote sensing image distribution system.The essential feature of the service is that customers can subscribe to data based on the location of interest and satellite image data received by antenna will be distributed to customer’s terminal devices instantly after imaging over the subscribed area.The workflow,architecture,and key technologies of the new generation data distribution system are described.The system is composed of four parts:data comprehensive processing component,data management component,product distribution component,and data display component.Based on this,a prototype system is developed,which demonstrates the promising service model with great potential for increased usage in many applications.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos. 61572376 and 91646206, and the National Key Research and Development Program of China under Grant No. 2016YFB1000603.
文摘The wide spread of location-based social networks brings about a huge volume of user check-in data, whichfacilitates the recommendation of points of interest （POIs）. Recent advances on distributed representation shed light onlearning low dimensional dense vectors to alleviate the data sparsity problem. Current studies on representation learningfor POI recommendation embed both users and POIs in a common latent space, and users＇ preference is inferred basedon the distance/similarity between a user and a POI. Such an approach is not in accordance with the semantics of usersand POIs as they are inherently different objects. In this paper, we present a novel translation-based, time and locationaware （TransTL） representation, which models the spatial and temporal information as a relationship connecting users andPOIs. Our model generalizes the recent advances in knowledge graph embedding. The basic idea is that the embedding ofa 〈time, location〉 pair corresponds to a translation from embeddings of users to POIs. Since the POI embedding shouldbe close to the user embedding plus the relationship vector, the recommendation can be performed by selecting the top-kPOIs similar to the translated POI, which are all of the same type of objects. We conduct extensive experiments on tworeal-world data.sets. The results demonstrate that our TransTL model achieves the state-of-the-art performance. It is alsomuch more robust to data sparsity than the baselines.
基金supported by the National Natural Science Foundation of China(Grant No.62172350)the Fundamental Research Funds for the Central Universities(No.21621028)the Innovation Project of GUET Graduate Education(No.2022YCXS083).
文摘Since smartphones embedded with positioning systems and digital maps are widely used,location-based services(LBSs)are rapidly growing in popularity and providing unprecedented convenience in people’s daily lives;however,they also cause great concern about privacy leakage.In particular,location queries can be used to infer users’sensitive private information,such as home addresses,places of work and appointment locations.Hence,many schemes providing query anonymity have been proposed,but they typically ignore the fact that an adversary can infer real locations from the correlations between consecutive locations in a continuous LBS.To address this challenge,a novel dual privacy-preserving scheme(DPPS)is proposed that includes two privacy protection mechanisms.First,to prevent privacy disclosure caused by correlations between locations,a correlation model is proposed based on a hidden Markov model(HMM)to simulate users’mobility and the adversary’s prediction probability.Second,to provide query probability anonymity of each single location,an advanced k-anonymity algorithm is proposed to construct cloaking regions,in which realistic and indistinguishable dummy locations are generated.To validate the effectiveness and efficiency of DPPS,theoretical analysis and experimental verification are further performed on a real-life dataset published by Microsoft,i.e.,GeoLife dataset.
基金the Centre for Spatial Data Infrastructures and Land Administration and the Department of Infrastructure Engineering at the University of Melbournethe University of Melbourne itselfthe Natural Sciences and Engineering Research Council of Canada for their support of the research conducted for this paper.
文摘The authors compare key elements of the emerging field of Indoor Location-Based Services(Indoor LBS)to those currently found in spatial data infrastructure(SDI)programs.After a brief review of SDIs and Location-Based Services,the corresponding drivers,characteristics and emerging issues within the field of Indoor LBS are introduced and discussed.A comparative framework relates the two in terms of the criteria‘People’,‘Data’,‘Technologies’,‘Standards’and‘Policies/Institutional Arrangements’.After highlighting key similarities and differences,the authors suggested three areas–definition of common framework datasets in Indoor LBS,more effective use of volunteered geographic information by SDI programs and development of appropriate privacy policies by both communities–that may benefit from sharing‘lessons learned’.
文摘A novel testing framework for location based services is introduced. In particular, the paper showcases a novel architecture for such a framework. The implementation of the framework illustrates both the functionality and the feasibility of the framework proposed and the utility of the architecture. The new framework is evaluated through comparison to several other methodologies currently available for the testing of location-based applications. A case study is presented in which the testing framework was applied to a typical mobile service tracking system. It is concluded that the proposed testing framework achieves the best coverage of the entire location based service testing problem of the currently available methodologies; being equipped to test the widest array of application attributes and allowing for the automation of testing activities.
基金supported by grants from the National Natural Science Foundation of China[grant numbers 41830645,41971331].
文摘The rising prosperity of Location-based Social Networks(LBSNs)witnessed an explosion in the availability of geo-tagged social media data,which enables tremendous location-aware online services,especially next point of interest(POI)recommendation.However,previous next POI recommendation studies usually adopt fix-length time windows for user check-in sequence modeling,leading to a limited capacity in capturing fine-grained user temporal preferences that easily change over time.Besides,existing methods often directly leverage multi-modal contexts as auxiliary to alleviate the data sparsity issue,which fails to fully exploit the sequential patterns of contextual information for inferring user interest drift.To address the above challenges,we propose a novel framework named iTourSPOT which extends traditional collaborative filtering methods with a context-aware POI embedding architecture.For enhancing temporal interests modeling capacity,we associate the context feature extraction with varying-length sessions and incorporate check-in frequencies of POIs as prior knowledge to instruct the session representation learning of our model.Moreover,a collaborative sequence transduction model is designed for joint context sequence modeling and session-based POI recommendation.Experimental results on a real-world geo-tagged photo dataset clearly demonstrate the effectiveness of the proposed framework when compared with state-of-the-art baseline methods,especially in both sparse and cold-start scenarios.
基金This work was supported by the National Science Foundation under Grant CNS-2007995 and Grant CNS-2008145。
文摘Ubiquitous information exchange is achieved among connected vehicles through the increasingly smart environment.The concept of conventional vehicular ad hoc network is gradually transformed into the Internet of vehicles(IoV).Meanwhile,more and more locationbased services(LBSs)are created to provide convenience for drivers.However,the frequently updated location information sent to the LBS server also puts user location privacy at risk.Thus,preserve user location privacy while allowing vehicles to have high-quality LBSs is a critical issue.Many solutions have been proposed in the literature to preserve location privacy.However,most of them cannot provide real-time LBS with accurate location updates.In this paper,we propose a novel location privacy-preserving scheme,which allows vehicles to send accurate real-time location information to the LBS server while preventing being tracked by attackers.In the proposed scheme,a vehicle utilizes the location information of selected shadow vehicles,whose route diverge from the requester,to generate multiple virtual trajectories to the LBS server so as to mislead attackers.Simulation results show that our proposed scheme achieves a high privacy-preserving level and outperforms other state-of-the-art schemes in terms of location entropy and tracking success ratio.
基金This study was supported by the National Natural Sci-ence Foundation of China(Grant Nos.61462017,61363005,U1501252,61662013)Guangxi Natural Science Foundation of China(2017GXNS-FAA 198035,2014GXNSFAA118353,2014GXNSFAA118390)+1 种基金Guangxi Key Laboratory of Automatic Detection Technology and Instrument Foun-dation(YQ15110)Guangxi Cooperative Innovation Center of Cloud Computing and Big Data,and the High Level Innovation Team of Colleges and Universities in Guangxi and Outstanding Scholars Program Funding.
文摘Many location-based services need to query objects existing in a specific space,such as location-based tourism resource recommendation.Both a large number of spatial objects and the real-time object access requirements of location-based services pose a big challenge for spatial object storage and query management.In this paper,we propose HGeoHashBase,an improved storage model by integrating GeoHash with key-value structure,to organize spatial objects for efficient range queries.GeoHash is responsible for spatial encoding and key-value structure as underlying data storage.Both the similarity of the encodings for objects in the close geographical locations and the multi-version data mechanism are blended into the proposed model well.Considering the tradeoff between encoding precision and query performance,a theoretical proof is presented.Extensive experiments are designed and conducted,whose results show that the proposed model can gain significant performance improvement.
