WebFig. 5. The decoupled model of BlockFed. The whole system can be divided into a blockchain subsystem and a federated learning subsystem with interactions as follows: (1) the federated learning subsystem uploads the local models to the blockchain subsystem, and (2) the blockchain subsystem returns the updated global model and rewards to the … WebFL-Block allows local learning updates of end devices exchanges with a blockchain-based global learning model, which is verified by miners. Built upon this, FL-Block enables the autonomous machine learning without any centralized authority to maintain the global model and coordinates by using a Proof-of-Work consensus mechanism of the blockchain.
Electronics Free Full-Text Secure Information Sharing Approach …
WebBlockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles IEEE Transactions on Vehicular Technology 2024-04 Journal article DOI: 10.1109/TVT.2024.2973651 Contributors : Yunlong Lu; Xiaohong Huang; Ke Zhang; Sabita Maharjan; Yan Zhang Show more detail Source : Crossref WebIn recent times, there has been a trend of moving away from a centralized approach to a decentralized approach, for example, using Blockchain to facilitate secure data sharing and traceability of critical information. er60su インク
Communication-Efficient Federated Learning and …
WebFeb 13, 2024 · A Blockchain Empowered Asynchronous Federated Learning scheme was developed in [2] for increasing the security and efficiency of data sharing between … WebHighlights • A brief overview of blockchain and the metaverse is presented. ... Alrashoud M., Hossain M.S., Blockchain-empowered trusted networking for unmanned aerial vehicles in the ... Shang B., Dong M., Blockchain-enabled secure data sharing scheme in mobile-edge computing: an asynchronous advantage actor–critic learning approach, IEEE ... WebOct 1, 2024 · Blockchain-enabled secure data sharing scheme in mobile-edge computing: an asynchronous advantage ActorCCritic learning approach. ... Blockchain empowered asynchronous federated learning for secure data sharing in Internet of Vehicles. IEEE Trans. Veh. Technol., 69 (4) (2024), pp. 4298-4311. er-5 マックエイト