Survey on the Convergence of Machine Learning and Blockchain
- URL: http://arxiv.org/abs/2201.00976v1
- Date: Tue, 4 Jan 2022 04:47:45 GMT
- Title: Survey on the Convergence of Machine Learning and Blockchain
- Authors: Shengwen Ding, Chenhui Hu
- Abstract summary: Machine learning (ML) has been pervasively researched nowadays and it has been applied in many aspects of real life.
However, issues of model and data still accompany the development of ML.
With the utilization of blockchain, these problems can be efficiently solved.
- Score: 4.45999674917158
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Machine learning (ML) has been pervasively researched nowadays and it has
been applied in many aspects of real life. Nevertheless, issues of model and
data still accompany the development of ML. For instance, training of
traditional ML models is limited to the access of data sets, which are
generally proprietary; published ML models may soon be out of date without
update of new data and continuous training; malicious data contributors may
upload wrongly labeled data that leads to undesirable training results; and the
abuse of private data and data leakage also exit. With the utilization of
blockchain, an emerging and swiftly developing technology, these problems can
be efficiently solved. In this paper, we conduct a survey of the convergence of
collaborative ML and blockchain. We investigate different ways of combination
of these two technologies, and their fields of application. We also discuss the
limitations of current research and their future directions.
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