Adaptive time-bound access control for internet of things in fog computing architecture

Author(s):  
Noran AboDoma ◽  
Eman Shaaban ◽  
Ahmad Mostafa
Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2110
Author(s):  
Desire Ngabo ◽  
Dong Wang ◽  
Celestine Iwendi ◽  
Joseph Henry Anajemba ◽  
Lukman Adewale Ajao ◽  
...  

The recent developments in fog computing architecture and cloud of things (CoT) technology includes data mining management and artificial intelligence operations. However, one of the major challenges of this model is vulnerability to security threats and cyber-attacks against the fog computing layers. In such a scenario, each of the layers are susceptible to different intimidations, including the sensed data (edge layer), computing and processing of data (fog (layer), and storage and management for public users (cloud). The conventional data storage and security mechanisms that are currently in use appear to not be suitable for such a huge amount of generated data in the fog computing architecture. Thus, the major focus of this research is to provide security countermeasures against medical data mining threats, which are generated from the sensing layer (a human wearable device) and storage of data in the cloud database of internet of things (IoT). Therefore, we propose a public-permissioned blockchain security mechanism using elliptic curve crypto (ECC) digital signature that that supports a distributed ledger database (server) to provide an immutable security solution, transaction transparency and prevent the patient records tampering at the IoTs fog layer. The blockchain technology approach also helps to mitigate these issues of latency, centralization, and scalability in the fog model.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Andre Henrique Mayer ◽  
Vinicius Facco Rodrigues ◽  
Cristiano Andre Da Costa ◽  
Rodrigo Da Rosa Righi ◽  
Alex Roehrs ◽  
...  

Author(s):  
Muhammad Rusyadi Ramli ◽  
Sanjay Bhardwaj ◽  
Dong-Seong Kim

Reliability is essential in industrial networks. In addition, most of the data from nodes of industrial Internet of Things (IIoT) are generated in real time. Thus, those data are mainly used for the time-sensitive applications. Furthermore, device failures should be considered when modeling reliable fog computing for IIoT. In this paper, we provide fundamental aspects to model reliable fog computing for IIoT. First, existing models of fog computing are compared. Then, the most feasible communication type to achieve a reliable system is determined from model analysis. Interaction modes are elaborated to study the advantages and drawbacks when communication is deployed in fog computing for IIoT, and challenges and solutions for reliable fog computing are discussed.


Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4807 ◽  
Author(s):  
Rabeea Basir ◽  
Saad Qaisar ◽  
Mudassar Ali ◽  
Monther Aldwairi ◽  
Muhammad Ikram Ashraf ◽  
...  

Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a comprehensive review of methods and techniques in fog computing. Our focus is on fog infrastructure and protocols in the context of IIoT applications. This article has two main research areas: In the first half, we discuss the history of industrial revolution, application areas of IIoT followed by key enabling technologies that act as building blocks for industrial transformation. In the second half, we focus on fog computing, providing solutions to critical challenges and as an enabler for IIoT application domains. Finally, open research challenges are discussed to enlighten fog computing aspects in different fields and technologies.


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