Searchable　symmetric　encryption　(SSE)　enables　a　user　to　outsource　a　private　dataset　to　a　cloud　server　in　encrypted　form　while　retaining　the　ability　to　search　over　the　encrypted　outsourced　data.　The　existing　SSE　schemes　improve　the　search　and　safety　performances　from　different　perspectives.　However,　almost　none　of　the　existing　SSE　schemes　considers　the　data　distribution　issues.　We　find　that　when　the　dataset　is　not　distributed　uniformly,　the　search　quality　based　on　the　conventional　methods　decreases.　Therefore,　the　existing　SSE　schemes　cannot　guarantee　high　search　quality　when　faced　with　non-uniform　datasets.　In　addition,　most　existing　SSE　solutions　cannot　hide　the　distribution　of　the　query　set.　In　this　article,　we　design　a　S\ecure　similarity　search　over　Encrypted　Non-uniform　and　high-dimensional　Datasets　(SEND)　with　a　novel　way　to　enhance　security.　The　basic　idea　is　to　combine　SSE　with　locality-sensitive　hashing　(LSH).　Unlike　earlier　schemes,　SEND　uses　selective　hashing,　which　has　better　performance　for　non-uniform　datasets.　Also,　we　present　a　novel　approach　to　hide　the　distribution　of　the　query　set,　which　makes　SEND　more　secure.　Our　experimental　results　indicate　SEND　achieves　a　high　search　quality　of　recall　and　precision,　and　it　is　proven　secure　against　adaptively　chosen　query　attacks　in　the　standard　model.