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A Recommender System for Robust Smart Contract Template Classification

IoT environments are becoming increasingly heterogeneous in terms of their distributions and included entities by collaboratively involving not only data centers known from Cloud computing but also the different types of third-party entities that can provide computing resources. To transparently pro...

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Detalles Bibliográficos
Autores principales: Gec, Sandi, Stankovski, Vlado, Lavbič, Dejan, Kochovski, Petar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866539/
https://www.ncbi.nlm.nih.gov/pubmed/36679436
http://dx.doi.org/10.3390/s23020639
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author Gec, Sandi
Stankovski, Vlado
Lavbič, Dejan
Kochovski, Petar
author_facet Gec, Sandi
Stankovski, Vlado
Lavbič, Dejan
Kochovski, Petar
author_sort Gec, Sandi
collection PubMed
description IoT environments are becoming increasingly heterogeneous in terms of their distributions and included entities by collaboratively involving not only data centers known from Cloud computing but also the different types of third-party entities that can provide computing resources. To transparently provide such resources and facilitate trust between the involved entities, it is necessary to develop and implement smart contracts. However, when developing smart contracts, developers face many challenges and concerns, such as security, contracts’ correctness, a lack of documentation and/or design patterns, and others. To address this problem, we propose a new recommender system to facilitate the development and implementation of low-cost EVM-enabled smart contracts. The recommender system’s algorithm provides the smart contract developer with smart contract templates that match their requirements and that are relevant to the typology of the fog architecture. It mainly relies on OpenZeppelin, a modular, reusable, and secure smart contract library that we use when classifying the smart contracts. The evaluation results indicate that by using our solution, the smart contracts’ development times are overall reduced. Moreover, such smart contracts are sustainable for fog-computing IoT environments and applications in low-cost EVM-based ledgers. The recommender system has been successfully implemented in the ONTOCHAIN ecosystem, thus presenting its applicability.
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spelling pubmed-98665392023-01-22 A Recommender System for Robust Smart Contract Template Classification Gec, Sandi Stankovski, Vlado Lavbič, Dejan Kochovski, Petar Sensors (Basel) Article IoT environments are becoming increasingly heterogeneous in terms of their distributions and included entities by collaboratively involving not only data centers known from Cloud computing but also the different types of third-party entities that can provide computing resources. To transparently provide such resources and facilitate trust between the involved entities, it is necessary to develop and implement smart contracts. However, when developing smart contracts, developers face many challenges and concerns, such as security, contracts’ correctness, a lack of documentation and/or design patterns, and others. To address this problem, we propose a new recommender system to facilitate the development and implementation of low-cost EVM-enabled smart contracts. The recommender system’s algorithm provides the smart contract developer with smart contract templates that match their requirements and that are relevant to the typology of the fog architecture. It mainly relies on OpenZeppelin, a modular, reusable, and secure smart contract library that we use when classifying the smart contracts. The evaluation results indicate that by using our solution, the smart contracts’ development times are overall reduced. Moreover, such smart contracts are sustainable for fog-computing IoT environments and applications in low-cost EVM-based ledgers. The recommender system has been successfully implemented in the ONTOCHAIN ecosystem, thus presenting its applicability. MDPI 2023-01-05 /pmc/articles/PMC9866539/ /pubmed/36679436 http://dx.doi.org/10.3390/s23020639 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gec, Sandi
Stankovski, Vlado
Lavbič, Dejan
Kochovski, Petar
A Recommender System for Robust Smart Contract Template Classification
title A Recommender System for Robust Smart Contract Template Classification
title_full A Recommender System for Robust Smart Contract Template Classification
title_fullStr A Recommender System for Robust Smart Contract Template Classification
title_full_unstemmed A Recommender System for Robust Smart Contract Template Classification
title_short A Recommender System for Robust Smart Contract Template Classification
title_sort recommender system for robust smart contract template classification
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866539/
https://www.ncbi.nlm.nih.gov/pubmed/36679436
http://dx.doi.org/10.3390/s23020639
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