Internet　of　things　(IoT)　has　been　widely　used　in　various　fields　because　of　the　high　intelligence　and　diversity.　IoT　security　features　sensory　information,　network　environments,　and　user　requirements.　Based　on　multilayer　multidimensional　characteristics　of　IoT　security　elements　and　security-oriented　system　indexes,　this　paper　adopted　an　autonomic　idea　of　＂cluster　user＂　collaboration　to　incorporate　the　concept　of　autonomic　discipline　to　fine-tune　＂single　user＂　processes　and　improve　overall　security　performance　in　multilayer　security　elements.　That　is,　from　microscopic　to　perception　layer,　from　singular　to　plural,　autonomic　configurations　and　adjustments　were　implemented,　which　achieved　self-renewal　and　optimization　of　the　overall　system　security.　A　multidimensional　constrained　optimization　method　was　adopted　to　realize　perception　layer　configuration　optimization.　During　the　process,　the　configuration　requirements　were　fed　back　to　cluster　users　in　each　layer;　accordingly,　security　configuration　optimization　was　triggered　from　the　perception　layer　perspective.　In　this　way,　self-configuration　and　the　ability　to　self-adjust　were　improved.　The　simulation　results　showed　that　without　affecting　its　general　significance　(randomly　assigned　weight),　the　presented　method　controlled　the　optimization　cost　in　a　small　range　[3.3181,　6.96626]　while　at　the　same　time　it　was　able　to　optimize　the　perception　layer　security　performance　by　more　than　39%.