Smart　city　refers　to　the　information　system　with　Internet　of　things　and　cloud　computing　as　the　core　technology　and　government　management　and　industrial　development　as　the　core　content,　forming　a　large-scale,　heterogeneous　and　dynamic　distributed　Internet　of　things　environment　between　different　Internet　of　things.　There　is　a　wide　demand　for　cooperation　between　equipment　and　management　institutions　in　the　smart　city.　Therefore,　it　is　necessary　to　establish　a　trust　mechanism　to　promote　cooperation,　and　based　on　this,　prevent　data　disorder　caused　by　the　interaction　between　honest　terminals　and　malicious　terminals.　However,　most　of　the　existing　research　on　trust　mechanism　is　divorced　from　the　Internet　of　things　environment,　and　does　not　consider　the　characteristics　of　limited　computing　and　storage　capacity　and　large　differences　of　Internet　of　things　devices,　resulting　in　the　fact　that　the　research　on　abstract　trust　mechanism　cannot　be　directly　applied　to　the　Internet　of　things;　On　the　other　hand,　various　threats　to　the　Internet　of　things　caused　by　security　vulnerabilities　such　as　collision　attacks　are　not　considered.　Aiming　at　the　security　problems　of　cross　domain　trusted　authentication　of　Intelligent　City　Internet　of　things　terminals,　a　cross　domain　trust　model　(CDTM)　based　on　self-authentication　is　proposed.　Unlike　most　trust　models,　this　model　uses　self-certified　trust.　The　cross-domain　process　of　internet　of　things　(IoT)　terminal　can　quickly　establish　a　trust　relationship　with　the　current　domain　by　providing　its　trust　certificate　stored　in　the　previous　domain　interaction.　At　the　same　time,　in　order　to　alleviate　the　collision　attack　and　improve　the　accuracy　of　trust　evaluation,　the　overall　trust　value　is　calculated　by　comprehensively　considering　the　quantity　weight,　time　attenuation　weight　and　similarity　weight.　Finally,　the　simulation　results　show　that　CDTM　has　good　anti　collusion　attack　ability.　The　success　rate　of　malicious　interaction　will　not　increase　significantly.　Compared　with　other　models,　the　resource　consumption　of　our　proposed　model　is　significantly　reduced.