There is an emerging recognition of the importance of utilizing contextual information in authorization decisions. Controlling access to resources in the field of wireless and mobile networking require the definition ...There is an emerging recognition of the importance of utilizing contextual information in authorization decisions. Controlling access to resources in the field of wireless and mobile networking require the definition of a formal model for access control with supporting spatial context. However, traditional RBAC model does not specify these spatial requirements. In this paper, we extend the existing RBAC model and propose the SC-RBAC model that utilizes spatial and location-based information in security policy definitions. The concept of spatial role is presented, and the role is assigned a logical location domain to specify the spatial boundary. Roles are activated based on the current physical position of the user which obtsined from a specific mobile terminal. We then extend SC-RBAC to deal with hierarchies, modeling permission, user and activation inheritance, and prove that the hierarchical spatial roles are capable of constructing a lattice which is a means for articulate multi-level security policy and more suitable to control the information flow security for safety-critical location-aware information systems. Next, con- strained SC-RBAC allows express various spatial separations of duty constraints, location-based cardinality and temporal constraints for specify fine-grained spatial semantics that are typical in location-aware systems. Finally, we introduce 9 in- variants for the constrained SC-RBAC and its basic security theorem is proven. The constrained SC-RBAC provides the foundation for applications in need of the constrained spatial context aware access control.展开更多
We introduce a new method for visualizing and analyzing information landscapes of ideas and events posted on public web pages through customized web-search engines and keywords.This research integrates GIScience and w...We introduce a new method for visualizing and analyzing information landscapes of ideas and events posted on public web pages through customized web-search engines and keywords.This research integrates GIScience and web-search engines to track and analyze public web pages and their web contents with associated spatial relationships.Web pages searched by clusters of keywords were mapped with real-world coordinates(by geolocating their Internet Protocol addresses).The resulting maps represent web information landscapes consisting of hundreds of populated web pages searched by selected keywords.By creating a Spatial Web Automatic Reasoning and Mapping System prototype,researchers can visualize the spread of web pages associated with specific keywords,concepts,ideas,or news over time and space.These maps may reveal important spatial relationships and spatial context associated with selected keywords.This approach may provide a new research direction for geographers to study the diffusion of human thought and ideas.A better understanding of the spatial and temporal dynamics of the‘collective thinking of human beings’over the Internet may help us understand various innovation diffusion processes,human behaviors,and social movements around the world.展开更多
Structured study of spatial objects and their relationships leads to a better cognition of the geospatial information and creates the concept of context at a higher level of abstraction.This study is aimed at providin...Structured study of spatial objects and their relationships leads to a better cognition of the geospatial information and creates the concept of context at a higher level of abstraction.This study is aimed at providing a comprehensive definition of the context for geospatial objects.A combination of binary qualitative spatial relationships(i.e.direction,distance,and topological relations)among the members of a set of spatial objects will be used accordingly.In addition,by incorporating the general concept of context,obtained from either static data(attributes in a database)or dynamic data(sensors),the compact context of spatial objects will be introduced.Our framework for presentation of the involved knowledge and conception about the objects in context is also explored using ontology and description logic because of powerful conceptualization of relationships,either spatial or non-spatial,integrally.For this purpose,the hierarchies of main structure and object properties are formed at first.The constraint and characteristics of classes,such as subclasses,equivalent classes,cardinality etc.,and object properties,such as being functional,transitive,symmetric,asymmetric,inverse functional,disjoint etc.,are discovered and presented in more detail using web ontology language in description logic mode.The implementation is then performed in the framework of semantic web and extensible markup language syntaxes.The method ultimately facilitates,spatial reasoning by effective querying in a semantic framework taking pellet reasoner and SPARQL(a recursive acronym for SPARQL Protocol and RDF Query Language).展开更多
Recently,the focus of semantic segmentation research has shifted to the aggregation of context prior and refined boundary.A typical network adopts context aggregation modules to extract rich semantic features.It also ...Recently,the focus of semantic segmentation research has shifted to the aggregation of context prior and refined boundary.A typical network adopts context aggregation modules to extract rich semantic features.It also utilizes top-down connection and skips connections for refining boundary details.But it still remains disadvantage,an obvious fact is that the problem of false segmentation occurs as the object has very different textures.The fusion of weak semantic and low-level features leads to context prior degradation.To tackle the issue,we propose a simple yet effective network,which integrates dual context prior and spatial propagation-dubbed DSPNet.It extends two mainstreams of current segmentation researches:(1)Designing a dual context prior module,which pays attention to context prior again with a shortcut connection.(2)The network can inherently learn semantic aware affinity values for each pixel and refine the segmentation.We will present detailed comparisons,which perform on PASCAL VOC 2012 and Cityscapes.The result demonstrates the validation of our approach.展开更多
文摘There is an emerging recognition of the importance of utilizing contextual information in authorization decisions. Controlling access to resources in the field of wireless and mobile networking require the definition of a formal model for access control with supporting spatial context. However, traditional RBAC model does not specify these spatial requirements. In this paper, we extend the existing RBAC model and propose the SC-RBAC model that utilizes spatial and location-based information in security policy definitions. The concept of spatial role is presented, and the role is assigned a logical location domain to specify the spatial boundary. Roles are activated based on the current physical position of the user which obtsined from a specific mobile terminal. We then extend SC-RBAC to deal with hierarchies, modeling permission, user and activation inheritance, and prove that the hierarchical spatial roles are capable of constructing a lattice which is a means for articulate multi-level security policy and more suitable to control the information flow security for safety-critical location-aware information systems. Next, con- strained SC-RBAC allows express various spatial separations of duty constraints, location-based cardinality and temporal constraints for specify fine-grained spatial semantics that are typical in location-aware systems. Finally, we introduce 9 in- variants for the constrained SC-RBAC and its basic security theorem is proven. The constrained SC-RBAC provides the foundation for applications in need of the constrained spatial context aware access control.
文摘We introduce a new method for visualizing and analyzing information landscapes of ideas and events posted on public web pages through customized web-search engines and keywords.This research integrates GIScience and web-search engines to track and analyze public web pages and their web contents with associated spatial relationships.Web pages searched by clusters of keywords were mapped with real-world coordinates(by geolocating their Internet Protocol addresses).The resulting maps represent web information landscapes consisting of hundreds of populated web pages searched by selected keywords.By creating a Spatial Web Automatic Reasoning and Mapping System prototype,researchers can visualize the spread of web pages associated with specific keywords,concepts,ideas,or news over time and space.These maps may reveal important spatial relationships and spatial context associated with selected keywords.This approach may provide a new research direction for geographers to study the diffusion of human thought and ideas.A better understanding of the spatial and temporal dynamics of the‘collective thinking of human beings’over the Internet may help us understand various innovation diffusion processes,human behaviors,and social movements around the world.
文摘Structured study of spatial objects and their relationships leads to a better cognition of the geospatial information and creates the concept of context at a higher level of abstraction.This study is aimed at providing a comprehensive definition of the context for geospatial objects.A combination of binary qualitative spatial relationships(i.e.direction,distance,and topological relations)among the members of a set of spatial objects will be used accordingly.In addition,by incorporating the general concept of context,obtained from either static data(attributes in a database)or dynamic data(sensors),the compact context of spatial objects will be introduced.Our framework for presentation of the involved knowledge and conception about the objects in context is also explored using ontology and description logic because of powerful conceptualization of relationships,either spatial or non-spatial,integrally.For this purpose,the hierarchies of main structure and object properties are formed at first.The constraint and characteristics of classes,such as subclasses,equivalent classes,cardinality etc.,and object properties,such as being functional,transitive,symmetric,asymmetric,inverse functional,disjoint etc.,are discovered and presented in more detail using web ontology language in description logic mode.The implementation is then performed in the framework of semantic web and extensible markup language syntaxes.The method ultimately facilitates,spatial reasoning by effective querying in a semantic framework taking pellet reasoner and SPARQL(a recursive acronym for SPARQL Protocol and RDF Query Language).
文摘Recently,the focus of semantic segmentation research has shifted to the aggregation of context prior and refined boundary.A typical network adopts context aggregation modules to extract rich semantic features.It also utilizes top-down connection and skips connections for refining boundary details.But it still remains disadvantage,an obvious fact is that the problem of false segmentation occurs as the object has very different textures.The fusion of weak semantic and low-level features leads to context prior degradation.To tackle the issue,we propose a simple yet effective network,which integrates dual context prior and spatial propagation-dubbed DSPNet.It extends two mainstreams of current segmentation researches:(1)Designing a dual context prior module,which pays attention to context prior again with a shortcut connection.(2)The network can inherently learn semantic aware affinity values for each pixel and refine the segmentation.We will present detailed comparisons,which perform on PASCAL VOC 2012 and Cityscapes.The result demonstrates the validation of our approach.
