As　a　new　trusted　data　sharing　pattern　with　privacy　protection,　the　integration　mechanism　of　blockchain　and　Federated　Learning　has　attracted　extensive　attention.　Generally,　this　mechanism　uses　blockchain　technology　to　supervise　the　original　data　and　calculation　results,　which　ignores　the　supervision　of　the　Federated　Learning　model　and　computing　process.　Therefore,　we　introduce　the　concepts　of　the　sandbox　and　state　channel　to　construct　a　new　data　privacy　sharing　paradigm　via　Blockchain　and　Federated　Learning.　Under　this　paradigm,　we　use　state　channel　to　connect　Blockchain　and　Federated　Learning.　And　state　channel　is　used　to　create　a　＇trusted　sandbox＇　to　instantiate　Federated　Learning　tasks　in　the　trustless　edge　computing　environment.　Meanwhile,　we　also　mainly　solve　problems　about　data　privacy　sharing　in　Federated　Learning　and　system　performance　degradation　caused　by　data　quality.　The　simulation　results　show　that　the　proposed　method　has　better　performance　and　efficiency　than　the　traditional　data　sharing　method.　　©　1968-2012　IEEE.