The invention discloses a federal learning incentive method and
system based on a
license chain, and relates to the technical field of blockchains, and the method comprises the steps that the registration and
authentication of clients is carried out, the registration of each
client is carried out to the
license chain, and the
authentication and
certificate issuing of each
client is carried out through the
license chain; the
smart contract of the license chain runs, and sampling is carried out from a group of clients meeting qualification requirements; the
client downloads the training model and the program from the license chain; the client updates parameters of the model by executing a
training program in local calculation, encrypts the updated parameters and uploads the encrypted parameters to the license chain; the license chain node receives the data encrypted by the client, decrypts the data and verifies the
correctness of the data; the license chain node carries out
consensus, after the
consensus is passed, the reputation value and the contribution value of the client are calculated, and a new block is generated; the intelligent contract aggregates the
model parameters and updates the parameters; and the
smart contract judges whether a preset convergence condition of the model is met, if not, the next round of training is carried out, if yes, training is terminated, and excitation is issued according to the contribution value of the client. According to the method and
system, the license block chain and the intelligent contract technology are applied, the problem that a federal learning malicious client or participants damage the
correctness of training by utilizing wrong gradient collection and parameter updating is solved, an incentive mechanism is provided, the enthusiasm of providing data and updating
network model parameters among the participants is increased, and meanwhile, the security of private data is improved.