مقاله انگلیسی یک چارچوب امن اینترنت اشیای صنعتی برای مدیریت منابع
Abstract
Introduction
Related work
Proposed framework
Simulation results and discussions
Conclusion
References
ABSTRACT
The Industrial Internet of Things (IIoT) can transform an existing isolated industrial system to a connected network. The IIoT and the related wireless connectivity requirements for industrial sensors are very significant. The deployed sensors in IIoT monitors the conditions of the industrial devices and machines. Therefore, reliability and security become the most important concerns in IIoT. This introduces many familiar and ever-increasing risks associated with the industrial system. The IIoT devices can be vulnerable to vast array of viruses, threats, and attacks. Therefore, an efficient protection strategy is required to ensure that the millions of IIoT devices are safe from these risks. However, resource constraint IIoT devices have not been designed to have effective security features. Due to this, in recent years, cloud, fog, and edge-based IIoT has received great attention in the research community. The computationally intensive tasks such as security, data analytics, decision making, and reporting are performed at the cloud or fog using a powerful computing infrastructure. The data security of the IIoT device has been provided by employing improved Rivest-ShamirAdelman (RSA) and hash signatures. The proposed RSA algorithm has a four-prime number of 512- bits. The device authentication is performed by employing a hash signature. For long network life, an efficient clustering technique for the sensor devices which is based on node degree(N), distance from the cluster(D), residual energy(R), and fitness (NDRF) has been proposed. The fitness of the sensor nodes is computed using the Salp swarm algorithm (SSA). In order to reduce the latency and communication overhead for IIoT devices a resource scheduling using SoftMax deep neural network (DNN) is proposed. All the requests coming from the cluster head are classified using SoftMax-DNN for best resource scheduling on the basis of storage, computing, and bandwidth requirements. The proposed framework produces superior results, especially in terms of energy consumption, latency, and strength of security.
INTRODUCTION
Technologies like the Internet of things (IoT), wireless sensor network (WSN), Cloud computing, edge computing, cyberphysical system, and fog computing, brings new business model and market. These technologies have several advantages in increasing automation, production, performance, reliability, and safety in industrial sectors. There is a growing possibility of adding more and more efficient, complex IP-based devices which use advanced sensors, wireless network, and microprocessors. In many sectors, the IoT has drawn the attention that includes retail, logistics, healthcare, The associate editor coordinating the review of this manuscript and approving it for publication was Chunsheng Zhu . supply chain, manufacturing, and pharmaceuticals. On the other hand, progress in wireless communications and sensor network technologies involves more and more connected objects in the Industrial Internet of things (IIoT) [1], [2]. Industry 5.0 standards promote the entire industry with regard to productivity, efficiency, promoting heterogeneous data, increased production, automation, and information integration [3]–[6]. In addition, the number of devices connected between them will drastically increase, and devices will communicate constantly with local cloud services in order to function smartly and flexibly. In particular, the IIoT system has a frequency, exchange of information and an independent financial transaction, which have always been very stagnant and highly isolated [7], [8]