Anti-Counterfeiting and Traceability Mechanism Based on Blockchain

Tan, Jun; Goyal, Saurabh

doi:10.3233/apc210189

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…The tamper-evident and traceability nature of the blockchain provides a good channel for data transmission. The flow of data is transparent and visible, which is very helpful for auditing [32].…”

Section: Comparison and Discussionmentioning

confidence: 99%

BSPPF: Blockchain‐Based Security and Privacy Preventing Framework for Data Middle Platform in the Era of IR 4.0

Chen

Goyal

Ramaswamy

2022

Journal of Nanomaterials

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Security and privacy issues about Big Data have emerged as one of the most pressing concerns in both academic circles and the business world in the era of IR 4.0. These worries are made worse because businesses are beginning to construct their own Big Data-based Data Middle Platform. The research team has summarized the security and privacy protection issues of Big Data-based Data Middle Platform by combining previous research and providing a table that lists some contributions that the blockchain uses for security and privacy protection in Big Data. A general Data Middle Platform architecture is also be given in the Methodology section. Based on this architecture, the team unveiled blockchain-based security and privacy protection framework on the Data Middle Platform in this study. This approach emphasizes mitigating the security and privacy issues posed by sensitive data entering the Data Middle Platform and data published by the Data Middle Platform. Following that, the researchers developed a testing system based on this framework to determine whether or not the framework was both feasible and practicable. The trials revealed that the framework is applicable, even though it requires further development and refinement.

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Section: Comparison and Discussionmentioning

confidence: 99%

BSPPF: Blockchain‐Based Security and Privacy Preventing Framework for Data Middle Platform in the Era of IR 4.0

Chen

Goyal

Ramaswamy

2022

Journal of Nanomaterials

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“…Rajesh [24] have developed that A block chain-based anti-counterfeiting traceability system can guarantee the consistency and correctness of the data kept by each participating node, safeguard the data's legitimacy, guarantee the quality of the product, increase businesses' credibility, and increase consumers' faith in their offerings. Nevertheless, the integration of block chain with the conventional anti-counterfeiting traceability mode has various issues, including low efficiency, because of the restricted system throughput, high energy consumption, and inadequate data availability.…”

Section: Methodsmentioning

confidence: 99%

Artwork Traceability and Anti-Counterfeiting Model Based on Block Chain Technology

Rui Yin

2024

jes

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The Chinese art market fostered the advancement of culture and spirituality. Nevertheless, false and counterfeit artwork is not uncommon. The art technology and security introduce the innovative method to determine Artwork Traceability and Anti-Counterfeiting. The aim of the work is to prevent the creation and circulation of fake or unauthorized copies of artworks. Because of the cryptographic security and immutability of block chains, it would be challenging to falsify artwork records or make accurate duplicates. This would foster confidence in the art market and shield collectors and artists from monetary losses and harm to their reputations. The data on mobile Application Data Center (ADC) platform and the cleansing the data using sub-aperture keystone transform matched filtering (SAKTMF) and the preprocessed data is fed into the Hierarchically Gated Recurrent Neural Network (HGRNN) classify the art work and Anti-Counterfeiting. The Bald Eagle Search Optimization (BES) Algorithm is used to optimize the weight parameter of HGRNN. The proposed model is implemented in MATLAB/ Simulink platform and the accuracy is compared to various existing approaches such as Dual-Branch Multi-Scale Feature Fusion network (DMF-Net), Region Convolutional Neural Network (R-CNN) and practical Byzantine fault tolerance (PBFT) algorithm. The gained results of the proposed HGRNN-BES method attains higher accuracy 97%, 96%, and 99%, higher precision 98%, 99%, and 97%.

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Anti-Counterfeiting and Traceability Mechanism Based on Blockchain

Cited by 2 publications

References 13 publications

BSPPF: Blockchain‐Based Security and Privacy Preventing Framework for Data Middle Platform in the Era of IR 4.0

BSPPF: Blockchain‐Based Security and Privacy Preventing Framework for Data Middle Platform in the Era of IR 4.0

Artwork Traceability and Anti-Counterfeiting Model Based on Block Chain Technology

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