Access Control at Triple Level: Specification and Enforcement of a Simple RDF Model to Support Concurrent Applications in Smart Environments

D’Elia, Alfredo; Honkola, Jukka; Manzaroli, Daniele; Cinotti, Tullio Salmon

doi:10.1007/978-3-642-22875-9_6

Cited by 23 publications

(8 citation statements)

References 11 publications

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“…It provides basic operations to smart space (query, insert, remove, update, subscribe and unsubscribe) with the use of triple representation as an instance of the Triple class. In addition this class also provides methods to setup and remove triples protection [5]. This protection is used to restrict changing of agent description, its output and state triples by other dataflow network nodes.…”

Section: Framework Architecturementioning

confidence: 98%

RoDaFlow: A framework for development of dataflow network agents in Smart-M3 with substitution method

Laure

Paramonov

2013

14th Conference of Open Innovation Association FRUCT

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The paper describes RoDaFlow-a framework for development of dataflow network agents on Smart-M3 platform. The agents created with the use of the framework support the substitution mechanism that allows to keep the dataflow network based systems in working conditions when some of its agents fall out. The RoDaFlow framework is implemented in Java with the use of Smart-M3 Java KPI library. It allows to develop primary and substitute agents by implementing only their programs, which define how agents process incoming information. The paper also describes a prototype of home light control system based on the dataflow network that allows to effectively control the light in a home. This system uses a number of sensors, actuators, remote control units and computational agents. The agents use information from remote control units and sensors to control the actuators and thus the light level in the home rooms. The agents for the prototype were developed with the use of proposed framework.

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Section: Framework Architecturementioning

confidence: 98%

RoDaFlow: A framework for development of dataflow network agents in Smart-M3 with substitution method

Laure

Paramonov

2013

14th Conference of Open Innovation Association FRUCT

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“…Since provenance data are typically stored in relational databases or RDF stores, one approach to access control is to leave the access control to the storage security mechanisms. Security for database technologies has been studied extensively in the past (see [50] for an overview) and the increasing need for maintaining semantic resources has developed a large set of works focused on security for RDF data [51,52,53].…”

Section: Securitymentioning

confidence: 99%

Implementing interoperable provenance in biomedical research

Ćurčin

Miles

Dánger

et al. 2014

Future Generation Computer Systems

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The provenance of a piece of data refers to knowledge about its origin, in terms of entities and actors involved in its creation, e.g. data sources used, operations carried out on them, and users enacting those operations. Provenance is used to better understand the data and the context of its production, and to assess its reliability, by asserting whether correct procedures were followed. Providing evidence for validating research is of particular importance in the biomedical domain, where the strength of the results depends on the data sources and processes used. In recent times, previously manual processes have become fully or semi-automated, e.g. clinical trial recruitment, epidemiological studies, diagnosis making. The latter is typically achieved through interactions of heterogeneous software systems in multiple settings (hospitals, clinics, academic and industrial research organisations). Provenance traces of these software need to be integrated in a consistent and meaningful manner, but since these software systems rarely share a common platform, the provenance interoperability between them has to be achieved on the level of conceptual models. It is a non-trivial matter to determine where to start in making a biomedical software system provenance-aware. In this paper, we specify recommendations to developers on how to approach provenance modelling, capture, security, storage and querying, based on our expe- * riences with two large-scale biomedical research projects: Translational Research and Patient Safety in Europe (TRANSFoRm) and Electronic Health Records for Clinical Research (EHR4CR). While illustrated with concrete issues encountered, the recommendations are sufficiently high level so as to be reusable across the biomedical domain.

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“…These approaches include approaches where access control is implemented as an additional layer on top of the repository, as in [42], and approaches where access-control information has also been integrated into repositories. In the triple-level access control [43], RDF resources are protected with access-restriction properties. Essentially, these properties are links to access policy graphs that specify the owner of the RDF resource as well as those predicates to which this protection applies.…”

Section: Access Control Over Semantic Informationmentioning

confidence: 99%

Architecture and Knowledge-Driven Self-Adaptive Security in Smart Space

2013

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Dynamic and heterogeneous smart spaces cause challenges for security because it is impossible to anticipate all the possible changes at design-time. Self-adaptive security is an applicable solution for this challenge. This paper presents an architectural approach for security adaptation in smart spaces. The approach combines an adaptation loop, Information Security Measuring Ontology (ISMO) and a smart space security-control model. The adaptation loop includes phases to monitor, analyze, plan and execute changes in the smart space. The ISMO offers input knowledge for the adaptation loop and the security-control model enforces dynamic access control policies. The approach is novel because it defines the whole adaptation loop and knowledge required in each phase of the adaptation. The contributions are validated as a part of the smart space pilot implementation. The approach offers reusable and extensible means to achieve adaptive security in smart spaces and up-to-date access control for devices that appear in the space. Hence, the approach supports the work of smart space application developers

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Access Control at Triple Level: Specification and Enforcement of a Simple RDF Model to Support Concurrent Applications in Smart Environments

Cited by 23 publications

References 11 publications

RoDaFlow: A framework for development of dataflow network agents in Smart-M3 with substitution method

RoDaFlow: A framework for development of dataflow network agents in Smart-M3 with substitution method

Implementing interoperable provenance in biomedical research

Architecture and Knowledge-Driven Self-Adaptive Security in Smart Space

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