The　application　of　Intelligent　Internet　of　Things　(IIoT)　in　constructing　distribution　station　areas　strongly　supports　platform　transformation,　upgrade,　and　intelligent　integration.　The　sensing　layer　of　IIoT　comprises　the　edge　convergence　layer　and　the　end　sensing　layer,　with　the　former　using　intelligent　fusion　terminals　for　real-time　data　collection　and　processing.　However,　the　influx　of　multiple　low-voltage　in　the　smart　grid　raises　higher　demands　for　the　performance,　energy　efficiency,　and　response　speed　of　the　substation　fusion　terminals.　Simultaneously,　it　brings　significant　security　risks　to　the　entire　distribution　substation,　posing　a　major　challenge　to　the　smart　grid.　In　response　to　these　challenges,　a　proposed　dynamic　and　energy-efficient　trust　measurement　scheme　for　smart　grids　aims　to　address　these　issues.　The　scheme　begins　by　establishing　a　hierarchical　trust　measurement　model,　elucidating　the　trust　relationships　among　smart　IoT　terminals.　It　then　incorporates　multidimensional　measurement　factors,　encompassing　static　environmental　factors,　dynamic　behaviors,　and　energy　states.　This　comprehensive　approach　reduces　the　impact　of　subjective　factors　on　trust　measurements.　Additionally,　the　scheme　incorporates　a　detection　process　designed　for　identifying　malicious　low-voltage　end　sensing　units,　ensuring　the　prompt　identification　and　elimination　of　any　malicious　terminals.　This,　in　turn,　enhances　the　security　and　reliability　of　the　smart　grid　environment.　The　effectiveness　of　the　proposed　scheme　in　pinpointing　malicious　nodes　has　been　demonstrated　through　simulation　experiments.　Notably,　the　scheme　outperforms　established　trust　metric　models　in　terms　of　energy　efficiency,　showcasing　its　significant　contribution　to　the　field.　©　2024　Tech　Science　Press.　All　rights　reserved.