With　the　advancement　of　mobile　Internet,　cloud　computing,　and　smart　sensing　devices,　location-based　services　(LBSs)　have　become　more　and　more　indispensable　in　the　Internet-of-Things　(IoT)-based　smart　cities.　Especially,　spatial　keyword　queries　have　been　widely　deployed　in　real-life　applications　in　recent　years.　Recently,　several　privacy-preserving　spatial　keyword　queries　schemes　were　proposed　to　guarantee　data　security　and　query　privacy　on　outsourced　data.　However,　these　schemes　support　neither　dynamic　update　nor　diverse　query　types,　which　cannot　meet　the　requirements　in　practical　applications.　This　article　proposes　two　secure　dynamic　spatial　keyword　queries　(SDSKQs)　constructions　that　support　expressive　query　types　and　dynamic　update.　First,　we　present　a　basic　SDSKQ　construction　based　on　hidden-vector　encryption　and　order-revealing　encryption.　Specifically,　we　propose　a　secure　hybrid　index　structure　for　spatio-textual　data,　named　encrypted　textual　signature　quadtree　(ETSQ-tree).　Using　ETSQ-tree,　the　server　can　prune　the　index　tree　according　to　search　queries　to　reduce　the　search　space.　Besides,　the　ETSQ-tree　can　be　updated　dynamically.　To　resist　the　file-injection　attack,　which　aims　to　infer　query　information　according　to　newly　inserted　objects,　we　further　improve　the　basic　SDSKQ　to　achieve　forward　security.　We　implement　our　two　constructions　and　evaluate　them　using　real-world　data　sets.　The　experimental　results　show　that　they　are　efficient　and　feasible　in　practical　applications,　and　the　comparative　evaluation　confirms　that　the　performance　of　our　constructions　outperforms　that　of　the　state-of-the-art　schemes.