In　recent　years,　with　the　rapid　development　of　the　Internet　of　Things　(IoT),　the　information　technology　has　been　widely　used　in　smart　home　applications.　On　the　other　hand,　smart　home　technology　closely　related　to　people’s　privacy,　which　is　not　much　considered　by　smart　home　vendors,　making　the　privacy　protection　of　smart　home　a　hot　research　topic.　Traditional　encryption　methods　can　ensure　the　security　of　the　transmission　process,　but　it　can　hardly　resist　the　side　channel　attacks.　Adversaries　can　analyze　the　radio　frequency　signals　of　wireless　sensors　and　timestamp　series　to　acquire　the　Activity　of　Daily　Living　(ADL).　The　most　simple　and　efficient　way　to　counter　side　channel　attacks　is　to　add　noise　into　the　transmitted　data　sequence.　In　this　paper,　we　propose　an　improved　method　based　on　Logistic　Regression　(LR),　which　can　be　adapted　to　network　status　to　protect　the　privacy　of　residents　in　smart　home　environments.　Compared　with　other　similar　approaches,　our　method　has　the　advantage　of　low　energy　consumption,　low　latency,　strong　adaptability　and　good　effect　of　privacy　protection.　©　2018,　ICST　Institute　for　Computer　Sciences,　Social　Informatics　and　Telecommunications　Engineering.