Accurate　prediction　of　the　trust　relationship　is　the　basis　for　trusted　access　and　secure　interaction　between　Internet　of　things　nodes.　To　evaluate　the　degree　of　trust,　a　trust　metric　is　assigned　to　every　node　depending　on　its　several　attributes.　Normal　nodes　in　Internet　of　things　tend　to　suffer　collusion　attacks　from　malicious　nodes;　thus,　the　accuracy　of　the　trust　measurement　decreases.　To　enhance　the　security　of　interaction　between　massive　Internet　of　things　nodes,　we　propose　a　multidimensional　attribute　trust　model　and　a　dynamic　maintenance　mechanism　of　a　trusted　group.　The　proposed　model　provides　a　reference　for　the　selection　and　evaluation　of　node　multidimensional　attribute　factors　to　adapt　to　different　Internet　of　things　application　scenarios.　The　dispersion　of　satisfaction　records　is　used　to　discover　abnormal　data　and　weaken　its　influence　on　the　calculation　of　the　node’s　comprehensive　trust　evaluation.　The　construction　of　trusted　groups　provides　an　architectural　foundation　for　the　application　of　group　signature　that　maintains　low　network　overhead.　The　performance　of　multidimensional　attribute　trust　model　and　dynamic　maintenance　mechanism　is　verified　using　Netlogo.　Simulation　results　show　the　efficiency　of　the　proposed　model　to　classify　the　malicious　nodes　and　honest　nodes,　as　well　as　to　build　a　trusted　group　that　could　ensure　honest　nodes　occupy　the　major　proportion.　©　The　Author(s)　2021.