Data　integrity　is　a　prerequisite　for　ensuring　data　availability　of　IoT　data　and　has　received　extensive　attention　in　the　field　of　IoT　big　data　security.　Stream　computing　systems　are　widely　used　in　the　field　of　IoT　for　real-time　data　acquisition　and　computing.　However,　the　real-time,　volatility,　suddenness,　and　disorder　of　stream　data　make　data　integrity　verification　difficult.　According　to　the　survey,　there　is　no　mature　and　universal　solution.　To　solve　this　issue,　we　constructed　a　data　integrity　verification　algorithm　scheme　of　the　stream　computing　system　(S-DIV)　by　utilizing　homomorphic　message　authentication　code　and　pseudo-random　function　security　assumption.　Furthermore,　based　on　S-DIV,　an　external　data　integrity　tracking　and　verification　system　is　constructed　to　track　and　analyze　the　message　data　stream　in　real　time.　By　verifying　the　data　integrity　of　message　during　the　whole　life　cycle,　the　problem　of　data　corruption　or　data　loss　can　be　found　in　time,　and　error　alarm　and　message　recovery　can　be　actively　implemented.　Then,　we　conduct　the　formal　security　analysis　under　the　standard　model　and,　finally,　implement　the　S-DIV　scheme　in　simulation　environment.　Experimental　results　show　that　the　scheme　can　guarantee　data　integrity　in　an　acceptable　time　without　affecting　the　efficiency　of　the　original　system.　©　2022　by　the　authors.