Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application
Abstract Blockchain technology (BT) allows market participants to keep track of digital transactions without central recordkeeping. The features of blockchain, including decentralization, persistency, and attack resistance, allow data security and privacy. Machine learning (ML) involves the analytic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2023-01-01
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| Series: | Discover Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44163-022-00046-0 |
| _version_ | 1797952398756413440 |
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| author | Hrag Jebamikyous Menglu Li Yoga Suhas Rasha Kashef |
| author_facet | Hrag Jebamikyous Menglu Li Yoga Suhas Rasha Kashef |
| author_sort | Hrag Jebamikyous |
| collection | DOAJ |
| description | Abstract Blockchain technology (BT) allows market participants to keep track of digital transactions without central recordkeeping. The features of blockchain, including decentralization, persistency, and attack resistance, allow data security and privacy. Machine learning (ML) involves the analytical platform on a massive amount of data to provide precise decisions. Since data reliability, integration, and data security are crucial in machine learning, the emergence of blockchain technology and machine learning has become a unique, most disruptive, and trending research in the last few years, achieving comparable and precise performance. The combination of blockchain and machine learning (BT–ML) has been applied across different applications to assist decision-makers in retrieving valuable data insights while preserving privacy and integration. This paper summarizes the state-of-the-art research in combing BT and ML in e-commerce and other various applications, including healthcare, smart transportation, and the Internet of Things (IoT). The challenges and benefits of integrating machine learning and blockchain technologies are outlined in the paper. We also discuss the advantages and limitations of current algorithms in the BT–ML integration. This paper provides a roadmap for researchers to pave the way for current and future research directions in combing the BT and ML research areas. |
| first_indexed | 2024-04-10T22:46:48Z |
| format | Article |
| id | doaj.art-2714d93c473a40c2baebb83f0d1562c9 |
| institution | Directory Open Access Journal |
| issn | 2731-0809 |
| language | English |
| last_indexed | 2024-04-10T22:46:48Z |
| publishDate | 2023-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Artificial Intelligence |
| spelling | doaj.art-2714d93c473a40c2baebb83f0d1562c92023-01-15T12:16:34ZengSpringerDiscover Artificial Intelligence2731-08092023-01-013111610.1007/s44163-022-00046-0Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and applicationHrag Jebamikyous0Menglu Li1Yoga Suhas2Rasha Kashef3Electrical, Computer, and Biomedical Engineering Department, Toronto Metropolitan UniversityElectrical, Computer, and Biomedical Engineering Department, Toronto Metropolitan UniversityElectrical, Computer, and Biomedical Engineering Department, Toronto Metropolitan UniversityElectrical, Computer, and Biomedical Engineering Department, Toronto Metropolitan UniversityAbstract Blockchain technology (BT) allows market participants to keep track of digital transactions without central recordkeeping. The features of blockchain, including decentralization, persistency, and attack resistance, allow data security and privacy. Machine learning (ML) involves the analytical platform on a massive amount of data to provide precise decisions. Since data reliability, integration, and data security are crucial in machine learning, the emergence of blockchain technology and machine learning has become a unique, most disruptive, and trending research in the last few years, achieving comparable and precise performance. The combination of blockchain and machine learning (BT–ML) has been applied across different applications to assist decision-makers in retrieving valuable data insights while preserving privacy and integration. This paper summarizes the state-of-the-art research in combing BT and ML in e-commerce and other various applications, including healthcare, smart transportation, and the Internet of Things (IoT). The challenges and benefits of integrating machine learning and blockchain technologies are outlined in the paper. We also discuss the advantages and limitations of current algorithms in the BT–ML integration. This paper provides a roadmap for researchers to pave the way for current and future research directions in combing the BT and ML research areas.https://doi.org/10.1007/s44163-022-00046-0BlockchainMachine learninge-commerceIoTHealthcareTransportations |
| spellingShingle | Hrag Jebamikyous Menglu Li Yoga Suhas Rasha Kashef Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application Discover Artificial Intelligence Blockchain Machine learning e-commerce IoT Healthcare Transportations |
| title | Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application |
| title_full | Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application |
| title_fullStr | Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application |
| title_full_unstemmed | Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application |
| title_short | Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application |
| title_sort | leveraging machine learning and blockchain in e commerce and beyond benefits models and application |
| topic | Blockchain Machine learning e-commerce IoT Healthcare Transportations |
| url | https://doi.org/10.1007/s44163-022-00046-0 |
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