Private Blockchain in Industrial IoT

Jo, Minho; Hu, Kai; Yu, Richard; Sun, Li; Conti, Mauro; Du, Qinghe

doi:10.1109/mnet.2020.9199796

Cited by 17 publications

(3 citation statements)

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“…However, there are a few challenges with the private blockchain that are observed from the state-of-the-art for various domains such as industrial IoT applications that we need to attack. These challenges are: (a) Compatibility with public blockchain, (b) Scalability, (c) Efficient consensus mechanisms, (d) secure access control, (e) Edge/fog computing networks, (f) robust smart contract, and (g) Replica management [83]. The working of the private blockchain is shown in Figure 3.…”

Section: Private Blockchain Technologymentioning

confidence: 99%

WITHDRAWN: Blockchain Technology with Deep Learning Adoptation for Various Applications: Vision and Future Opportunities

Afaq

Manocha

2022

Preprint

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A recent study has successfully focused on Deep Learning and Blockchain technologies because of their tremendous potential for producing reliable decisions. The bulk of contemporary deep learning techniques implemented on centralized servers gives operational transparency, traceability, reliability, security, and reliable data provenance qualities. Deep Learning models are therefore susceptible to the single point of failure problem since they are trained using centralized data. The advantages of merging Blockchain with Deep Learning algorithms are examined in this paper. Additionally, current research is examined to determine the best strategy to combine these two technologies for the best outcome.

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Section: Private Blockchain Technologymentioning

confidence: 99%

WITHDRAWN: Blockchain Technology with Deep Learning Adoptation for Various Applications: Vision and Future Opportunities

Afaq

Manocha

2022

Preprint

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“…In the process of this study, we found different challenges and questions, such as private blockchain usage. This model is becoming popular for private businesses and personal applications [40][41][42][43][44]. Nevertheless, the usage of public blockchain networks cannot be denied.…”

Section: Discussionmentioning

confidence: 99%

Asset Ownership Transfer and Inventory Using RFID UHF TAGS and Ethereum Blockchain NFTs

et al. 2023

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In the present, many organizations grow on a daily basis, using many assets to perform their activities and generate profit. In large organizations, all of these assets must be managed, occasionally leading to challenges depending on the organization’s size. For this reason, the role of asset custodian is needed. This role entails assigning the fixed assets to one person for their care, maintenance, and safekeeping. In this process, it is necessary to update information in the central system, leading to further administrative processes, which, in the majority of cases, are carried out through traditional methods. This involves time to obtain wet signatures, a great deal of paperwork, and time for the person or people in charge to update the information. Due to these reasons, the process can be updated partially or entirely to use digital means in order to solve the mentioned inconveniences. This paper presents a proof-of-concept system to offer a modernized and practical solution to this problem using the advantages of blockchain technology, and speeding up the process by using assets identified with UHF RFID technology to permit the reading of many tags that can be embedded and hidden with no need for line-of-sight, allowing fast ownership transfer, using smart contracts in the Ethereum private blockchain.

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“…Blockchain is a method to resolve the security problem of the digital data [32], [33]. Since it succussed in the Bitcoin system in 2009, and it was rapidly used in the agricultural supply chain because of the security and the transparency [34].…”

Section: Introductionmentioning

confidence: 99%

Wood Product Tracking Using an Improved AKAZE Method in Wood Traceability System

Sun

Cao

et al. 2021

IEEE Access

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The tracking of the wood product is an important technology in the trade activity of rare plants. Normally, factories use Quick Response (QR) and Radio-Frequency Identification (RFID) to identify the individual wood product, but these technologies are not safe enough because they can be easily falsified. The traditional methods are hard to catch the detail of the slim wood texture from the wood product. In this study, a novel method is employed to resolve these problems using a biometric feature on the surface of the real wood product to distinguish the individual wood product. AKAZE is used to extract the keypoint of wood texture. A sub-area detection technique along with a serialization method is then developed to improve the rate of identification. The sub-area detection technique deals with picking out a sub-region in which there are enough AKAZE points as small as possible. The serialization method is also utilized to reduce the redundant process of feature extraction. The experimental results demonstrate that the values of accuracy, recall, and F 1 reach 0.98, 0.96, and 0.96, respectively. The match time that uses serialized function is reduced to 1/3 of which has no application in the original image. Validated results also reveal that our proposed methodology improve the robustness of the wood product identification, and it can be used in Wood Traceability System (WTS) with the blockchain to resolve the digital trust problem and the fast distinction issues of the real wood product.

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Private Blockchain in Industrial IoT

Cited by 17 publications

References 0 publications

WITHDRAWN: Blockchain Technology with Deep Learning Adoptation for Various Applications: Vision and Future Opportunities

WITHDRAWN: Blockchain Technology with Deep Learning Adoptation for Various Applications: Vision and Future Opportunities

Asset Ownership Transfer and Inventory Using RFID UHF TAGS and Ethereum Blockchain NFTs

Wood Product Tracking Using an Improved AKAZE Method in Wood Traceability System

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