Data security sharing model based on privacy protection for blockchain‐enabled industrial Internet of Things

Zhang, Qikun; Li, Yongjiao; Wang, Ruifang; Liu, Lu; Tan, Yuan

doi:10.1002/int.22293

Cited by 39 publications

(20 citation statements)

References 32 publications

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“…It is necessary to limit and distinguish the applicable conditions of the data structure and model in some aspects, and carry out reasonable error analysis and data evaluation on the data structure and model on a certain basis. e corresponding in-depth data analysis and processing correlation analysis model is obtained, and its application level is more in depth [28].…”

Section: Deviation Analysis and Application Of Data Structure And Dat...mentioning

confidence: 99%

[Retracted] Applications of Deep Learning in the Evaluation and Analysis of College Students’ Mental Health

Lan-feng

2022

Discrete Dynamics in Nature and Society

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It is an important research direction of mental health discipline in the current era to evaluate and analyze college students’ mental health by using deep learning methods and form visual data characteristics and analyzable discipline conclusions. Based on this, this paper carries out the research method of convolutional neural network by using the research concept of deep learning. Firstly, the paper summarizes the fast intelligent analysis model based on the convolutional neural network system algorithm, classifies and summarizes the unique characteristics of college students’ mental health, and uses the convolutional neural network processing model to analyze, evaluate, and observe college students’ mental health combined with the big data theory. Secondly, through the expansion and utilization of multi-layer neuron self-coding neural network, the psychological health of college students is evaluated and analyzed in the psychological discipline, the discrete data structure is established by using the relevant psychological data, the psychological behavior of college students is analyzed, summarized, and classified, and the data model is filled to judge the mental health status of college students. Finally, through the design of confirmatory experiments, the results show that the college students’ mental health evaluation and analysis model based on deep learning is more efficient in individual data analysis. Compared with the mode of analyzing college students’ mental health through in-depth learning, the traditional psychological research method has a large workload and is not suitable for the universality and consistency of college students. This paper solves this problem and provides a reference for relevant research.

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Section: Deviation Analysis and Application Of Data Structure And Dat...mentioning

confidence: 99%

[Retracted] Applications of Deep Learning in the Evaluation and Analysis of College Students’ Mental Health

Lan-feng

2022

Discrete Dynamics in Nature and Society

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“…It also proposes a specific conversion from AGKA without certificate authentication to AGKA without identity authentication based on session key. Group key agreement among intelligent terminals in intelligent system are proposed in Zhang et al 23,24 A scalable GKA protocol is proposed in Naresh et al 25 The flexible architecture proposed by the protocol not only reduces the process of cryptographic calculations, but also reduces the workload. The protocol adopts a hybrid and hierarchical approach to clusters, and the workload of key update is reduced without affecting other groups.…”

Section: Related Workmentioning

confidence: 99%

A group key agreement protocol for intelligent internet of things system

Zhang

Zhu

et al. 2021

Int J Intell Syst

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The application of intelligent computing in Internet of Things (IoTs) makes IoTs systems such as telemedicine, in-vehicle IoT, and smart home more intelligent and efficient. Secure communication and secure resource sharing among intelligent terminals are essential. A secure communication channel for intelligent terminals can be established through group key agreement (GKA), thereby ensuring the security communication and resource sharing for intelligent | ZHANG ET AL.

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“…There are limited works on distributed data storage on edge and fog resources, as reviewed and classified in Moyasiadis et al 13 We describe the decentralized storage solution from the perspectives of fog/edge computing. 7,9,11,3,14 FogStore 7 proposes a distributed key-value store on fog resources with replication and differential consistency. vStore 9 supports context-aware placement of data on fog and cloud resources, with mobile devices generating and consuming these data.…”

Section: Related Workmentioning

confidence: 99%

SmartStore: A blockchain and clustering based intelligent edge storage system with fairness and resilience

Chen

Zhou

et al. 2021

Int J of Intelligent Sys

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With the development of edge computing, edge storage solutions are attracting widespread attention. When facing the requirements of lower latency and faster access speed from end devices, edge storage solutions are considered to be an alternative to the cloud. However, edges are usually owned by small organizations which have limited operations and maintenance capabilities. This makes these edge devices can be easily disabled by external attacks or internal hardware failures. Besides, the heterogeneity of the edge devices will also make it difficult to price the edge resources uniformly. To tackle these problems, we propose SmartStore: an auction mechanism based on blockchain to allocate edge resources. Considering centralized solutions have access bottlenecks and trust issues, we built SmartStore on the smart contract. With Bayesian game theory, SmartStore can analyze how data owners (DO) and edges price the resources can maximize their benefits. From an economic perspective, both DO and edges can make full use of edge heterogeneous resources with SmartStore. Besides, a two‐stage submission strategy is proposed to complete the sealed auction. Furthermore, considering the reliability of edge storage, we propose a cluster‐based block distribution algorithm for SmartStore's intelligent edge recommendation process. SmartStore ensures the reliability of edge storage while maximizing the benefits and resource utilization of both parties. Finally, we conduct specific experiments on the proposed auction smart contract through “Ethereum” and the experimental results of implementation show the effectiveness and efficiency of our SmartStore.

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Data security sharing model based on privacy protection for blockchain‐enabled industrial Internet of Things

Cited by 39 publications

References 32 publications

[Retracted] Applications of Deep Learning in the Evaluation and Analysis of College Students’ Mental Health

[Retracted] Applications of Deep Learning in the Evaluation and Analysis of College Students’ Mental Health

A group key agreement protocol for intelligent internet of things system

SmartStore: A blockchain and clustering based intelligent edge storage system with fairness and resilience

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