With　the　continuous　advancement　of　the　construction　of　smart　campuses,　the　rapid　development　based　on　big　data　technology　has　greatly　promoted　the　construction　of　college　financial　sharing　platforms.　In　the　context　of　smart　campuses,　the　construction　of　the　network　security　system　of　the　financial　sharing　platform　for　colleges　at　this　stage　has　taken　a　step　forward.　With　the　rapid　development　of　information　technology,　the　great　data　technology,　artificial　intelligence　technology　and　other　technologies　shall　be　applied　for　the　construction　of　a　platform　for　the　exchange　of　resources　with　a　view　to　improving　the　security　of　the　platform　network.　This　paper　takes　smart　campus　as　the　theoretical　basis　of　the　research,　uses　big　data　technology　and　artificial　intelligence　technology　as　auxiliary　research,　and　integrates　its　main　content　to　analyze　and　research　the　improvement　of　the　network　security　construction　of　the　university＇s　financial　sharing　platform.　This　document　sets　out　as　a　research　subject　the　Financial　Distribution　Platform　of　the　University　of　Science　and　Technology,　collects　the　data　of　various　applications　in　the　school　financial　sharing　platform　system,　and　uses　the　K-means　clustering　algorithm　in　the　clustering　algorithm　to　characterize　the　network　security　level　of　the　university　financial　sharing　platform　Classification,　and　then　use　machine　learning　algorithms　to　perform　correlation　analysis　on　network　security.　Recognizing　the　important　role　of　the　early　warning　system　in　maintaining　network　security　and　the　ideological　security　of　university　finance,　system,　the　results　of　the　experimental　research　show　that　this　research　is　of　great　importance　for　maintaining　the　safety　performance　of　the　university　platform　network;　economic　distribution.　©　2021　ACM.