1,721,062 research outputs found
Privacy issues in location-aware browsing
Full text linkAdvances in positioning services and their pervasiveness, e.g., wi- based location services, pave the way to the development of innovative LBSs and architectures. In this paper
we focus on location-aware browsing, a framework which enables websites to acquire the position of website users. In particular we discuss privacy issues related to the recent
W3C proposal for a geolocation API standard. Such specication prescribes that users must give explicit consent to the disclosure of position information to websites. In this
paper we argue that stronger and more exible protection is needed: a) users should be provided with the capability of disclosing coarse regions in place of point coordinates in
order to limit the disclosure of personal location data; b) location information should be protected not only against websites but also against location service providers. We dis-
cuss a possible approach to address those requirements under the assumption that the position is computed by a wibased positioning service. Finally, we broaden the discussion
to include a complementary legal viewpoint
Third party geolocation services in LBS: privacy requirements and research issues
Full text linkThe advances in positioning technologies and the emergence of geolocation standards opens up to the development of innovative location-based services (LBS), e.g., web-based LBS. These services challenge existing privacy protection solutions. For example, the position information is provided by a third party, the location provider, and this party may be not fully trusted. In this paper, we analyze the web-based LBS model. Then we outline the privacy-aware geolocation strategy which minimizes the interaction with the untrusted location provider by caching the information that is useful to determine the position in proximity of the private positions, e.g., home, which have been already visited. The deployment of this strategy requires investigating several issues and novel tools. The objective of this paper is to discuss the technical challenges and suggest directions of research towards a comprehensive privacy-preserving framework. To our knowledge, this is the first work on privacy protection against untrusted location providers
Foreword for the special issue of selected papers from the 3rd ACM SIGSPATIAL Workshop on Security and Privacy in GIS and LBS
Full text linkThe third Workshop on Security and Privacy in GIS and LBS (SPRINGL 2010) was organized in November 2, 2010, San Jose, California in conjunction with the SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2010). Security and privacy are the two dimensions of GIS systems and geospatial applications that need to be addressed for these applications to have wider acceptance. However, we are still far from fully achieving this goal with provable techniques that can be adopted by the industry. The SPRINGL workshop series aims to provide a forum for researchers working in the field of geospatial data security and privacy to discuss the advances in this domain.
In order for solid archival work to be presented to the community, special issues of Transactions on Data Privacy have been organized for the previous SPRINGL workshops. This special issue contains three extended papers that have been selected from the papers presented at SPRINGL 2010 focusing mainly on the privacy aspects
Privacy issues in location-aware browsing : 3rd ACM SIGSPATIAL Workhop on Security and Privacy in GIS and LBS
No full textSpringl 2008 : proceedings of the SIGSPATIAL ACM Workshop on Security and Privacy in GIS and LBS : Irvine, California, USA, November 4, 2008
No full textSpatial trajectories segmentation: trends and challenges
No full textGiven a sequence S of temporally ordered observations, non necessarily of spatial nature, the segmentation task partitions S in a set of disjoint sub-sequences si, .., sn - the segments - such that ∪i∈[1, n] si = S. Typically, segments represents sub-sequences that are somehow homogeneous with respect to some criteria. Depending on the context and the nature of observations, segments can be given an approximated representation, for example segments can be assigned a descriptive label or one of the data points is chosen as representative of the whole sub-sequence. The final result is a summarized representation of the sequence. This simple and intuitive mechanism has been extensively studied in literature, for example, for the summarization of time series. Interestingly, the notion of segment is also at the basis of the most recent trajectory data models. For example, segments are the informative units in the semantic trajectories, where they are called episodes. Episodes are spatial sub-trajectories that can be semantically annotated using application-dependent descriptions, e.g. place names [1]. Similarly the recent symbolic trajectory data model [2] describes the individual movement as a sequence of temporally annotated labeled states s1, ..sn, where each state si is associated with a time interval. Beyond data modeling, segmentation can be employed for the indexing of trajectories in moving object databases while another major role is to support data analysis, especially for the extraction of individual mobility patterns. The concept of trajectory segment is thus emerging as shared and perhaps unifying concept across data modeling, indexing and analysis
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