With　the　continuous　expansion　of　Internet　of　Things　(IoT)　devices,　edge　computing　mode　has　emerged　in　recent　years　to　overcome　the　shortcomings　of　traditional　cloud　computing　mode,　such　as　high　delay,　network　congestion,　and　large　resource　consumption.　Thus,　edge-thing　systems　will　replace　the　classic　cloud-thing/cloud-edge-thing　systems　and　become　mainstream　gradually,　where　IoT　devices　can　offload　their　tasks　to　neighboring　edge　nodes.　A　common　problem　is　how　to　utilize　edge　computing　resources.　For　the　sake　of　fairness,　double　auction　can　be　used　in　the　edge-thing　system　to　achieve　an　effective　resource　allocation　and　pricing　mechanism.　Due　to　the　lack　of　third-party　management　agencies　and　mutual　distrust　between　nodes,　in　our　edge-thing　systems,　we　introduce　blockchains　to　prevent　malicious　nodes　from　tampering　with　transaction　records　and　smart　contracts　to　act　as　an　auctioneer　to　realize　resources　auction.　Since　the　auction　results　stored　in　this　blockchain-based　system　are　transparent,　they　are　threatened　with　inference　attacks.　Thus　in　this　paper,　we　design　a　differentially　private　combinatorial　dou-ble　auction　mechanism　by　exploring　the　exponential　mechanism　such　that　maximizing　the　revenue　of　edge　computing　platform,　in　which　each　IoT　device　requests　a　resource　bundle　and　edge　nodes　compete　with　each　other　to　provide　resources.　It　can　not　only　guarantee　approximate　truthfulness　and　high　revenue,　but　also　ensure　privacy　security.　Through　nec-essary　theoretical　analysis　and　numerical　simulations,　the　effectiveness　of　our　proposed　mechanisms　can　be　validated.(c)　2022　Elsevier　Inc.　All　rights　reserved.