As　the　Internet　of　Things　gathers　pace　and　popularity,　more　and　more　data　is　collected　at　the　edge.　To　unleash　the　value　of　data　and　make　it　tradable,　data　markets　have　been　proposed.　However,　existing　data　markets　generally　depend　on　broker　or　blockchain,　which　inevitably　raises　concerns　about　one　or　more　aspects　of　fairness,　security,　or　efficiency.　In　addition,　to　promote　data　trading　in　the　data　market,　a　data　trading　incentive　mechanism　is　also　essential.　In　this　paper,　we　propose　a　novel　data　trading　scheme　based　on　state　channels　and　Stackelberg　game.　Firstly,　we　propose　a　State　Channels-based　Data　Trading　(SCDT)　framework　to　support　non-repudiable　and　efficient　data　trading.　The　framework　can　arbitrate　disputes　arising　from　off-chain　data　trading　through　state　channels,　enabling　traders　to　conduct　efficient　transactions　off-chain　without　worrying　about　security　issues.　Secondly,　we　propose　an　optimal　incentive　mechanism　to　solve　the　pricing　and　purchasing　problems.　The　tripartite　interactions　among　the　data　seller,　resource　seller,　and　user　service　platform　are　formulated　as　a　Stackelberg　game　to　maximize　the　profits　of　all　participants.　Finally,　we　implement　the　data　trading　framework　and　analyze　the　incentive　mechanism,　which　reveals　the　feasibility　of　the　framework　and　the　rationality　of　the　incentive　mechanism.　IEEE