{"title":"Differential private trajectory protection of moving objects","authors":"Roland Assam, Marwan Hassani, T. Seidl","doi":"10.1145/2442968.2442977","DOIUrl":"https://doi.org/10.1145/2442968.2442977","url":null,"abstract":"Location privacy and security of spatio-temporal data has come under high scrutiny in the past years. This has rekindled enormous research interest. So far, most of the research studies that attempt to address location privacy are based on the k-Anonymity privacy paradigm. In this paper, we propose a novel technique to ensure location privacy in stream and non-stream mobility data using differential privacy. We portray incoming stream or non-stream mobility data emanating from GPS-enabled devices as a differential privacy problem and rigorously define a spatio-temporal sensitivity function for a trajectory metric space. Privacy is achieved through path perturbation in both the space and time domain. In addition, we introduce a new notion of Nearest Neighbor Anchor Resource to add more contextual meaning in the face of uncertainty to the perturbed trajectory path. Unlike k-Anonymity techniques that require more mobile objects to achieve strong anonymity; we show that our approach provides stronger privacy even for a single moving mobile object, outliers or mobile objects in sparsely populated regions.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123819066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A method for constructing 3D traveling routes from GPS navigation data","authors":"Tom Goren-Bar, J. Greenfeld","doi":"10.1145/2442968.2442980","DOIUrl":"https://doi.org/10.1145/2442968.2442980","url":null,"abstract":"In this paper we present a novel algorithm for constructing 3D vector maps for off road navigation using GPS track recordings. The algorithm treats the GPS track recordings as a point cloud and performs track clustering by iteratively aggregating the point cloud. The aggregation is done by simulating attraction forces between samples forming groups of points that belong to the same trail. Next, it constructs clusters centers out of the groups and forms center-lines that connect the cluster centers to create a 3D graph representation. Graph enrichments such as junction clarification are also applied. We demonstrate the results of our algorithm on a simulated dataset of ten tracks for verification purposes and on a dataset of actual GPS tracks of mountain bike trails. An analysis of the geodetic accuracy of the algorithm solution is given using ground control points which were measured in the field.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122749800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Techniques to protect privacy against inference attacks in location based services","authors":"D. Nussbaum, Masoud T. Omran, J. Sack","doi":"10.1145/2442968.2442976","DOIUrl":"https://doi.org/10.1145/2442968.2442976","url":null,"abstract":"In this paper, we study potential inference attacks targeting Location Based Service (LBS) users, and provide heuristic defense techniques to protect their privacy against such attacks.\u0000 Having access to supplemental information such as subsequent query times, speed limits/travel times on the underlying road-network, and/or the residential/commercial address directory, adversaries might be able to infer sensitive information such as location, identity, and/or lifestyle about the querying LBS user. To prevent adversaries from connecting external information to user queries, we apply various heuristic privacy-preserving algorithms whose objective is to alter user queries in order to protect users against inference attacks while providing exact results in a timely manner. Our algorithms enable users to customize their privacy levels based on individual's preferences through the use of flexible user-controlled parameters. For this, we introduce the novel notion of (i, j)-privacy.\u0000 We evaluate our algorithms experimentally on different road-networks varying a number of input parameters and present the results here. The outcomes of our experiments confirm that except for special cases where a high anonymity level is requested or queries are submitted with very high frequency, our algorithms provide quality results in less than few seconds.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125380952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MONET: modeling and querying moving objects in spatial networks","authors":"Lin Qi, Markus Schneider","doi":"10.1145/2442968.2442975","DOIUrl":"https://doi.org/10.1145/2442968.2442975","url":null,"abstract":"Data about moving objects is being collected in many different application domains with the help of sensor networks, and GPS-enabled devices. In most cases, the moving objects are not free to move, they are usually restricted by some spatial constraints such as Spatial Networks. Spatial networks are ubiquitous and have been widely used in transportation, traffic planning, navigation as well as in Geographical Information System (GIS) applications. In most scenarios, moving objects such as vehicles move along predefined spatial networks like transportation networks. Unfortunately, the concepts for modeling and querying objects in unconstrained spaces like an outdoor space cannot be transferred to constrained spaces like a road network due to the different features of the environments in which the spatial objects move. Further, modern positioning devices as well as mobile and sensor technology have led to large volumes of moving objects in spatial networks. Therefore, we need a database-friendly data model to explicitly model spatial networks and, more importantly, describe relative movements in these networks. In this paper, we propose a new two-layered data model called MONET (Moving Objects in NETworks) model. The lower layer is a data model for spatial networks. This data model is the prerequisite for the upper model that represents moving objects in these networks. This layered model fits well to formulate relationships between moving objects and a network in queries. A query language, called MONET QL (MONET Query Language), allows a clear description of and access to moving objects in spatial networks and to provides high-level operations on them.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115347763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Models for half-direction based part-whole relationships","authors":"Gaurav Singh, R. A. By","doi":"10.1145/2442968.2442972","DOIUrl":"https://doi.org/10.1145/2442968.2442972","url":null,"abstract":"We present a conceptual framework for interpreting text phrases such as \"in central northern Bahia\" and \"in northern central Bahia\" as spatial element of geographic information retrieved from text. Our approach allows spatial computations with such phrases, leading to deeper understanding of places and human spatial cognition associated with them. We develop a number of interpretation models and their placement based on different notions of centre of the reference region. We evaluate these models for the performance characteristics of precision and recall, against an Ornithological gazetteer of Brazil, and draw conclusions on the cognition of, and computation with half-direction based part-whole relations.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128919616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zdravko Galić, Emir Meskovic, K. Križanović, M. Baranović
{"title":"OCEANUS: a spatio-temporal data stream system prototype","authors":"Zdravko Galić, Emir Meskovic, K. Križanović, M. Baranović","doi":"10.1145/2442968.2442982","DOIUrl":"https://doi.org/10.1145/2442968.2442982","url":null,"abstract":"Recent advances in wireless communication, miniaturization of spatially enabled devices and global navigation satellite systems (GNSS) services have resulted in a large number of novel application domains. Applications in these novel domains (moving objects tracking, sensor networks, fleet management, real-time intelligent transportation systems, etc.) process huge volume of continuous streaming data, i.e. data that is produced incrementally over time, rather than being available in full before processing. Data stream management systems (DSMS) have been developed to manage continuous data streams. Usually based on relational paradigm, they have rudimentary support for spatial data. Recent research efforts in data stream management systems focus mainly on processing continuous queries over traditional data streams, and only a few papers addressed spatio-temporal continuous queries. In this paper we present OCEANUS, an ongoing effort to extend TelegraphCQ DSMS with spatial support providing a platform for spatio-temporal streaming applications.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"699 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132419643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using skyline query and information retrieval for implicit location and preference based recommendation","authors":"Qiang Pu, A. Lbath, Daqing He","doi":"10.1145/2442968.2442984","DOIUrl":"https://doi.org/10.1145/2442968.2442984","url":null,"abstract":"Location and preference based recommendation could provide mobile user with his personalized interesting information. Mobile user does not always provide all attributes of his preference or query, especially when he is moving. The recommendation system database also does not contain all attributes of user's needs. In order to provide possible interesting places when a user is moving, only according to his implicit preference and physical moving location without his providing preference or query explicitly, we proposed two circle concepts, one is physical position circle and the other is virtual preference circle. Those skyline query places in physical position circle which also match mobile user's implicit preference in virtual preference circle will be recommended. User's implicit preference will be estimated under language modeling framework according to user's historical visiting behaviors. Experiments show that our method that the combination of using skyline query and information retrieval to do an implicit location and preference based recommendation without user's providing explicit preference or query is effective for mobile users.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116731110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real-time route planning with stream processing systems: a case study for the city of Lucerne","authors":"Asli Özal, A. Ranganathan, Nesime Tatbul","doi":"10.1145/2064959.2064965","DOIUrl":"https://doi.org/10.1145/2064959.2064965","url":null,"abstract":"Traffic-aware real-time route planning has recently been an application of increasing interest for metropolitan cities with busy traffic. This paper approaches the problem from a stream processing point of view and proposes a general architecture to solve it. This work is inspired by a real use case and is implemented on an industry-strength stream processing engine. Experimental results on this implementation demonstrate the scalability of this approach in terms of increasing data and query rates.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115995431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"In-memory caching for fast stream history access","authors":"Gereon Schüller, R. Saul, Andreas Behrend","doi":"10.1145/2064959.2064968","DOIUrl":"https://doi.org/10.1145/2064959.2064968","url":null,"abstract":"In data stream systems, it is necessary to access the historical stream data. For example, in a CEP system historical data is necessary for deriving complex events where the underlying atomic events are distributed over a potentially long period of time. Historical stream data is also important in trend analysis systems where new or changed analysis criteria have to be checked on past data. The requirements for history access are manifold; it should be as fast as possible and ought to fit homogeneously into the existing system structure. The latter implies that the management of the constantly growing historical data is automatically performed by the system itself and data can be freely accessed using declarative queries. In this paper, we present an approach relying on the combination of a server-based DBMS and a client-based in-memory DBMS for accelerating access to GeoStream history. The recently developed \"Airspace Monitoring System\" (AIMS), that monitors and analyzes flight data streams in real time, will serve as a testbed for our approach. We show that an efficient and flexible video recorder and time slider functionality can be implemented using the suggested caching approach.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131842972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discovering patterns in traffic sensor data","authors":"F. Kashani, C. Shahabi, Bei Pan","doi":"10.1145/2064959.2064963","DOIUrl":"https://doi.org/10.1145/2064959.2064963","url":null,"abstract":"We maintain a one of a kind, large-scale and high resolution (both spatially and temporally) traffic sensor dataset collected from the entire Los Angeles County road network. Traffic sensors (installed under the road pavement) are used to measure real-time traffic flows through road segments. In this paper, we exploit this dataset to rigorously verify two popular instinctive understandings about traffic flows on road segments: 1) each road segment has a typical traffic flow (known by local travelers) and one can often categorize road segments based on the similarity of their traffic flows, and 2) the road segments within each category not only have similar traffic flows but also are similar in their other characteristics (such as locality, connectivity). Toward this end, we developed a hypothesis analysis framework based on a variety of clustering and correlation evaluation techniques and leveraged this framework to respectively show the following. First, the set of road segments can indeed be partitioned into a set of distinct subpartitions with similar traffic flows, and there is a limited number of signature traffic patterns/labels each of which can accurately represent all traffic flows of a subpartition of the road segments. Second, all segments within each subpartition (represented by one signature) are also highly similar in three other characteristics, namely, direction, connectivity and locality. Our experiments verify our observations with high confidence.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"34 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123148089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}