|
| Subject | Literature | Time | Contribution | Goal |
|
| Sharing applications | [41] | 2018 | Proposed a data collection scheme based on deep reinforcement learning | Smart mobile terminal data collection and sharing |
| [42] | 2019 | Used deep reinforcement learning to optimize the system’s cache resource utilization | Realize secure resource sharing in wireless network |
| [43] | 2020 | Selected nodes through deep reinforcement learning to improve the efficiency of federated learning | Solve the problem of collaborative training in the Internet of Vehicles |
| [44] | 2020 | Provides blockchain-based privacy preserving multimedia intelligent video surveillance | Ensure the integrity and security of cloud-based intelligent monitoring systems |
| [45] | 2019 | Integrated machine learning and natural language processing, which can detect different types of cardiovascular clinical data | Predict the type of illness and simplify the diagnosis process |
| [46] | 2018 | Proposed a data inspection module based on machine learning | Securely sharing personal information |
|
| Security applications | [47] | 2019 | Combined machine learning and fuzzing to detect contract vulnerabilities | Detect smart contract vulnerabilities |
| [48] | 2020 | Proposed a vulnerability detection model based on GNN | Detect smart contract vulnerabilities |
| [49] | 2019 | Proposed a detection framework based on deep reinforcement learning | Detect loopholes in the blockchain incentive mechanism |
| [50] | 2018 | Proposed a classification model combining data mining and machine learning | Detect Ponzi schemes in Ethereum |
| [51] | 2019 | Proposed a DOORChain model that integrates deep learning, ontology, and operations research | Detect malicious transactions in the blockchain |
|
| Transaction application | [52] | 2018 | Proposed two prediction models based on cyclic convolutional network and long short-term memory algorithm, respectively | Predict bitcoin price |
| [53] | 2019 | Proposed an association scheme based on binary classification | Bitcoin address correlation analysis |
| [54] | 2018 | Proposed a recognition scheme based on DNN | Bitcoin address-user identification |
|
| Deposit application | [55] | 2020 | Proposed a vaccine blockchain system integrated with machine learning | Vaccine supervision and recommendation |
| [56] | 2020 | Proposed a smart tram charging system based on consortium blockchain | Solve the problem of independent operation of energy companies and opaque charging information |
| [57] | 2018 | Designed a blockchain-based credit evaluation system | Strengthen the effectiveness of supervision and management of the food supply chain |
| [58] | 2019 | Designed an electronic voting system based on blockchain using intelligent agents | Guarantee the security of voting |
|
| Resource applications management | [59] | 2018 | Proposed an optimal auction mechanism based on deep learning | Edge computing resource allocation |
| [60] | 2019 | Proposed a new type of hierarchical reinforcement learning algorithm | Dynamic resource management of the IoT system |
| [63] | 2019 | Proposed an actor-critic algorithm with asynchronous advantages of stable training | Solve the computing offload problem of mobile edge computing |
| [64] | 2020 | Proposed a secure and intelligent vehicle task offloading strategy based on blockchain and learning algorithms | Reduce task delay and switching overhead under the premise of ensuring security, privacy, and fairness |
| [65] | 2020 | Proposed a resource management scheme based on deep reinforcement learning | System resource management |
| [66] | 2020 | Proposed a fusion model of blockchain and width learning | Forecast user energy demand |
| [67] | 2017 | Researched the smart resource management strategy of cloud data center based on blockchain | Save the energy cost |
|
| Scalability optimization applications | [68] | 2019 | Utilized machine learning to build a consensus committee | Improve blockchain scalability |
| [69] | 2020 | Addressed clustering and fragmentation based on k-means algorithm | Efficient fragmentation |
| [70] | 2019 | Designed a deep reinforcement learning algorithm to improve the scalability of the blockchain | Solve the scalability problem of the Industrial Internet of Things and improve throughput |
| [71] | 2020 | Combined federated learning to improve blockchain scalability | Design a secure federal edge learning system |
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