In　edge　computing　scenarios,　due　to　the　wide　distribution　of　devices,　complex　application　environments,　and　limited　computing　and　storage　capabilities,　their　authentication　and　access　control　efficiency　is　low.　To　address　the　above　issues,　a　secure　trusted　authentication　scheme　based　on　semantic　Long　Short-Term　Memory　(LSTM)　and　blockchain　is　proposed　for　IoT　applications.　The　attribute-based　access　control　model　is　optimized,　combining　blockchain　technology　with　access　control　models,　effectively　improving　the　robustness　and　credibility　of　access　control　systems.　Semantic　LSTM　is　used　to　predict　environmental　attributes　that　can　further　restrict　user　access　and　dynamically　meet　the　minimum　permission　granting　requirements.　Experiments　show　that　when　the　number　of　certificates　is　60,　the　computational　overhead　of　the　proposed　method　is　only　203s,　which　is　lower　than　other　state-of-the-art　methods.　Therefore,　the　performance　of　the　proposed　schema　in　information　security　protection　in　IoT　environments　shows　promise　as　a　scalable　authentication　solution　for　IoT　applications.