A Framework of Web Data Integrated LBS Middleware

In this paper, we propose a flexible locationbased service （LBS） middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge data source of location relative information, we integrate the common used web data extraction techniques into the middleware framework, exposing a unified web data interface for the upper applications to make them more attractive. Besides, the framework also emphasizes some common LBS issues, including positioning, location modeling, location-dependent query processing, privacy and secure management.

Representation and Organization for Spatial Data in LBS

Aiming at the special demand on SVG_based representation and organization for spatial data in location based services（LBS）, the research is made in this article on the conversion method from multiple formats to SVG format, and a harris_corner detector method is proposed and verified to evaluate the conversion result. Based on the above, an optimized compression arithmetic is proposed, which integrated the characteristic of code simplification and GZIP compression. The test shows that the techniques on conversion and compression are feasible, which means that SVG_based representation is suited for spatial data in LBS and the improved compression arithmetic is prior to the former.

Location,Localization,and Localizability

Location-aware technology spawns numerous unforeseen pervasive applications in a wide range of living, pro- duction, commence, and public services. This article provides an overview of the location, localization, and localizability issues of wireless ad-hoc and sensor networks. Making data geographically meaningful, location information is essential for many applications, and it deeply aids a number of network functions, such as network routing, topology control, coverage, boundary detection, clustering, etc. We investigate a large body of existing localization approaches with focuses on error control and network localizability, the two rising aspects that attract significant research interests in recent years. Error control aims to alleviate the negative impact of noisy ranging measurement and the error accumulation effect during coope- rative localization process. Network localizability provides theoretical analysis on the performance of localization approaches, providing guidance on network configuration and adjustment. We emphasize the basic principles of localization to under- stand the state-of-the-art and to address directions of future research in the new and largely open areas of location-aware technologies.

An efficient method for privacy preserving location queries

Recently, the issue of privacy preserving loca- tion queries has attracted much research. However, there are few works focusing on the tradeoff between location privacy preservation and location query information collection. To tackle this kind of tradeoff, we propose the privacy persevering location query （PLQ）, an efficient privacy pre-serving location query processing framework. This frame- work can enable the location-based query without revealing user location information. The framework can also facilitate location-based service providers to collect some information about the location based query, which is useful in practice. PLQ consists of three key components, namely, the location anonymizer at the client side, the privacy query processor at the server side, and an additional trusted third party connect- ing the client and server. The location anonymizer blurs the user location into a cloaked area based on a map-hierarchy. The map-hierarchy contains accurate regions that are parti- tioned according to real landforms. The privacy query pro- cessor deals with the requested nearest-neighbor （NN） loca- tion based query. A new convex hull of polygon （CHP） algo- rithm is proposed for nearest-neighbor queries using a poly- gon cloaked area. The experimental results show that our al- gorithms can efficiently process location based queries.

A Random Anonymity Framework for Location Privacy

Location k-anonymity techniques typically use anony- mous spatial region to ensure privacy. But these solutions are vul- nerable to multiple queries attacks and inference attacks. Failing to account for the obstacle in geographic space is a severe problem since adversaries will surely regard these constraints. A novel framework is proposed to enhance location-dependent queries, based on the theoretical work of k-anonymity and Voronoi diagrams, allows a user to express service requirement and privacy require- ment by specifying a region and an appropriate value ofk. A trusted anonymity server form a restricted set （k, r, s）, which is composed of a number of discrete points to meet the requirements for location k-anonymity and location /-diversity. The location-based services （LBS） server implements an efficient algorithm for continu- ous-region-query processing. Simulation results demonstrated that the framework is superior to previous works in terms of privacy. Moreover, discreteness and randomness of the anonymous set are conducive to resisting location tracking attacks.

Research on k-anonymity privacy protection scheme based on bilinear pairings

Aimed at enhancing privacy protection of location-based services（ LBS） in mobile Internet environment,an improved privacy scheme of high service quality on the basis of bilinear pairings theory and k-anonymity is proposed. In circular region of Euclidian distance,mobile terminal evenly generates some false locations,from which half optimal false locations are screened out according to position entropy,location and mapping background information. The anonymity obtains the effective guarantee,so as to realize privacy protection. Through security analyses,the scheme is proved not only to be able to realize such security features as privacy,anonymity and nonforgeability,but also able to resist query tracing attack. And the result of simulation shows that this scheme not only has better evenness in selecting false locations,but also improves efficiency in generating and selecting false nodes.