In　order　to　boost　the　accuracy　of　range　counting　queries　of　the　released　two-dimensional　space　data　under　differential　privacy,　an　algorithm　Quad-heu　based　on　quad-tree　for　differential　privacy　two-dimensional　data　publication　by　space　partitioning　was　proposed.　The　basic　idea　of　Quad-heu　is　to　firstly　construct　a　quad-tree　with　respect　to　the　two-dimensional　data　and　then　add　Laplace　noise　to　tree　nodes.　After　that,　a　bottom　up　heuristic　approach　for　structural　adjustment　of　the　quad-tree　was　put　forward,　and　the　aim　of　which　was　to　balance　the　noise　error　of　queries　and　the　error　of　uniform　hypothesis.　Finally,　the　accuracy　of　range　counting　queries　was　further　reduced　by　post-processing　the　tree　nodes＇　values　through　the　consistency　constraint　of　queries.　Experimental　analysis　was　designed　by　comparing　Quad-heu　and　the　traditional　algorithms　on　the　accuracy　of　range　counting　queries　in　the　released　data　and　the　algorithm　efficiency.　Experimental　results　show　that　Quad-heu　is　effective　and　feasible.　©　2016,　Editorial　Board　of　Journal　of　Huazhong　University　of　Science　and　Technology.　All　right　reserved.