Context-Aware Access Control Model for Cloud Computing

Zhou, Zhenji; Wu, Lifa; Zheng, Hong

doi:10.14257/ijgdc.2013.6.6.01

Cited by 10 publications

(5 citation statements)

References 13 publications

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“…In the cloud, the relation between users and resources is dynamic, so users and service providers might not be in the same security domain and hence identity-based securities such as Discretionary access control (DAC) or Mandatory access control (MAC) cannot be used in an open cloud computing environment. Zhou et al [91] proposed a new Context-Aware Access Control for cloud computing (CAACM) by considering platform trust level, spatial state and temporal state as context. The particular model determines mechanisms of authorization from cloud management role to objects allowing dynamic activation of role permission by identifying cloud management role with context.…”

Section: The Caac Approaches For Accessing Data From Edge Iot and CLmentioning

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 Caac Approaches For Accessing Data From Edge Iot and CLmentioning

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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“…The values and meanings of α and D j are the same as in Formula (9). As in Formula (9), N(t), C(t) and M(t) represent the usage of network bandwidth, CPU and memory at time t, respectively. Correspondingly, 1-N(t),1-C(t) and 1-M(t) represent the free percentage of these resources, respectively.…”

Section: N(t) Is the Network Bandwidth Usage C(t) Is The Cpu Usage mentioning

confidence: 99%

“…9, No. 1 (2016) [1][2][3][4][5][6][7][8][9] Co-published by Atlantis Press and Taylor & Francis Copyright: the authors 1 much more complicated than that in general network environments.…”

Section: Introductionmentioning

confidence: 99%

“…Ray et al introduced a graph-theoretic semantics of access control model to face challenges of cloud access control [8]. Zhou et al took the spatial state, temporal state and platform trust level as contexts to present a new context-aware access control model for cloud computing [9]. Tang et al presented a multi-tenant rolebased access control model which aims to provide fine-grained authorization in collaborative cloud environments by building trust relations among tenants [10].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Role-based Access Control Model in Cloud Environments

Jun¹,

Wang²,

Gong³

et al. 2016

IJCIS

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In Cloud environments, the relationship between resources and users is more ad hoc and dynamic. The role-based access control (RBAC) model is an appropriate access control model for Cloud environments. When using the RBAC model in Cloud environments, some new elements should be considered. This paper proposes a SAT-RBAC model (security and availability based trust relationship in RBAC) and adopts the following elements as the main factors of a trust relationship: the security state and network availability of the host used by a user, the protection state of the service providers that are related to the role. A security-based scheduling model for Cloud environments is presented. Because of the uncertainty of Cloud environments, the trust relationship is divided into three zones: the unbelievable zone, the probable believable zone and the believable zone. Bayesian method is used to estimate the trust probability distribution in the probable believable zone. This paper also provides algorithms to evaluate the values of the main elements of a trust relationship. Finally, the experiments in simulated Cloud environment based on CloudSim in PlanetLab are discussed and the results prove that the SAT-RBAC model is effective in filtering abnormal behaviors in Cloud environments.

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“…Cluster server adalah sekumpulan server independen yang beroperasi serta bekerja secara erat dan terlihat oleh klien jaringan seolah-olah server-server tersebut adalah satu buah unit server [5]. Kelebihan dari cluster server adalah kecepatan akses data yang lebih baik daripada server tunggal sehingga cluster server ini mempunyai kemampuan komputasi yang relatif baik.…”

Section: Cluster Serverunclassified

Implementasi Cluster Server pada Raspberry Pi dengan Menggunakan Metode Load Balancing

Putra

Winarno

2016

JEPIN

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Server merupakan bagian penting dalam sebuah layanan didalam jaringan komputer. Peran server dapat menentukan kualitas baik buruknya dari layanan tersebut. Kegagalan dari sebuah server bisa disebabkan oleh beberapa faktor diantaranya kerusakan perangkat keras, sistem jaringan serta aliran listrik. Salah satu solusi untuk mengatasi kegagalan server dalam suatu jaringan komputer adalah dengan melakukan clustering server. Tujuan dari penelitian ini adalah untuk mengukur kemampuan Raspberry Pi (Raspi) digunakan sebagai web server. Raspberry Pi yang digunakan menggunakan Raspberry Pi 2 Model B dengan menggunakan processor ARM Cortex-A7 berjalan pada frekuensi 900MHz dengan memiliki RAM 1GB. Sistem operasi yang digunakan pada Raspberry Pi adalah Linux Debian Wheezy. Konsep penelitian ini menggunakan empat buah perangkat Raspberry Pi dimana dua Raspi digunakan sebagai web server dan dua Raspi lainnya digunakan sebagai penyeimbang beban (Load Balancer) serta database server. Metode yang digunakan dalam pembangunan cluster server ini menggunakan metode load balancing, dimana beban server bekerja secara merata di masing-masing node. Pengujian yang diterapkan dengan melakukan perbandingan kinerja dari Raspbery Pi yang menangani lalu lintas data secara tunggal tanpa menggunakan load balancer serta pengujian Raspberry Pi dengan menggunakan load balancer sebagai beban penyeimbang antara anggota cluster server.

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Context-Aware Access Control Model for Cloud Computing

Abstract: Abstract

Cited by 10 publications

References 13 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

A Novel Role-based Access Control Model in Cloud Environments

Implementasi Cluster Server pada Raspberry Pi dengan Menggunakan Metode Load Balancing

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