Fine-Grained Access Control Within NoSQL Document-Oriented Datastores

Colombo, Pietro; Ferrari, Elena

doi:10.1007/s41019-016-0015-z

Cited by 28 publications

(28 citation statements)

References 19 publications

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“…Looking at the existing CAAC approaches, these solutions extensively have been used to access data and information resources from centralized sources [27,28]. These approaches do not provide adequate functionalities to access required data sets from distributed environments (e.g., distributed cloud centres).…”

Section: The Backgroundmentioning

confidence: 99%

A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues

Kayes

Kalaria

Sarker

et al. 2020

Sensors

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Over the last few decades, the proliferation of the Internet of Things (IoT) has produced an overwhelming flow of data and services, which has shifted the access control paradigm from a fixed desktop environment to dynamic cloud environments. Fog computing is associated with a new access control paradigm to reduce the overhead costs by moving the execution of application logic from the centre of the cloud data sources to the periphery of the IoT-oriented sensor networks. Indeed, accessing information and data resources from a variety of IoT sources has been plagued with inherent problems such as data heterogeneity, privacy, security and computational overheads. This paper presents an extensive survey of security, privacy and access control research, while highlighting several specific concerns in a wide range of contextual conditions (e.g., spatial, temporal and environmental contexts) which are gaining a lot of momentum in the area of industrial sensor and cloud networks. We present different taxonomies, such as contextual conditions and authorization models, based on the key issues in this area and discuss the existing context-sensitive access control approaches to tackle the aforementioned issues. With the aim of reducing administrative and computational overheads in the IoT sensor networks, we propose a new generation of Fog-Based Context-Aware Access Control (FB-CAAC) framework, combining the benefits of the cloud, IoT and context-aware computing; and ensuring proper access control and security at the edge of the end-devices. Our goal is not only to control context-sensitive access to data resources in the cloud, but also to move the execution of an application logic from the cloud-level to an intermediary-level where necessary, through adding computational nodes at the edge of the IoT sensor network. A discussion of some open research issues pertaining to context-sensitive access control to data resources is provided, including several real-world case studies. We conclude the paper with an in-depth analysis of the research challenges that have not been adequately addressed in the literature and highlight directions for future work that has not been well aligned with currently available research.

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Section: The Backgroundmentioning

confidence: 99%

A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues

Kayes

Kalaria

Sarker

et al. 2020

Sensors

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“…In many localized systems this is the case, however, in the IoT scenarios, the availability of the data contributes to most of the problems. Access control plays an important issue in data management and is a vivid topic in the recent literature [28,29,30]. Our platform builds on top of mechanisms, described in the literature and can take advantage of recent findings, especially those related to streaming platforms.…”

Section: Related Workmentioning

confidence: 99%

Streaming Data Fusion for the Internet of Things

Kenda

Kažić

Novak

et al. 2019

Sensors

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To achieve the full analytical potential of the streaming data from the internet of things, the interconnection of various data sources is needed. By definition, those sources are heterogeneous and their integration is not a trivial task. A common approach to exploit streaming sensor data potential is to use machine learning techniques for predictive analytics in a way that is agnostic to the domain knowledge. Such an approach can be easily integrated in various use cases. In this paper, we propose a novel framework for data fusion of a set of heterogeneous data streams. The proposed framework enriches streaming sensor data with the contextual and historical information relevant for describing the underlying processes. The final result of the framework is a feature vector, ready to be used in a machine learning algorithm. The framework has been applied to a cloud and to an edge device. In the latter case, incremental learning capabilities have been demonstrated. The reported results illustrate a significant improvement of data-driven models, applied to sensor streams. Beside higher accuracy of the models the platform offers easy setup and thus fast prototyping capabilities in real-world applications.

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“…Access control technologies will be more important in the future [149]. Contextual conditions bring new challenges to context-sensitive access control as context information will play a crucial role in dynamically changing environments [150]. As a promising example, recently an ontology-based approach that captures such contextual conditions and incorporates them into the policies, utilizing the ontology languages and the fuzzy logic-based reasoning has been presented [151].…”

Section: The Application Layermentioning

confidence: 99%

A Review of Semantic Sensor Technologies in Internet of Things Architectures

Honti

Abonyi

2019

Complexity

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Intelligent sensors should be seamlessly, securely, and trustworthy interconnected to enable automated high-level smart applications. Semantic metadata can provide contextual information to support the accessibility of these features, making it easier for machines and humans to process the sensory data and achieve interoperability. The unique overview of sensor ontologies according to the semantic needs of the layers of IoT solutions can serve a guideline of engineers and researchers interested in the development of intelligent sensor-based solutions. The explored trends show that ontologies will play an even more essential role in interlinked IoT systems as interoperability and the generation of controlled linkable data sources should be based on semantically enriched sensory data.

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Fine-Grained Access Control Within NoSQL Document-Oriented Datastores

Cited by 28 publications

References 19 publications

A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues

A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues

Streaming Data Fusion for the Internet of Things

A Review of Semantic Sensor Technologies in Internet of Things Architectures

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