With　the　development　of　cloud　computing,　data　owners　are　motivated　to　outsource　their　data　and　the　corresponding　complex　management　tasks　to　the　public　cloud　for　convenience　and　economic　savings.　In　order　to　protect　data　privacy,　data　owners　prefer　to　outsource　their　sensitive　data　in　an　encrypted　form　to　the　cloud,　which　makes　the　traditional　search　techniques　useless.　Searchable　encryption　is　a　technique　to　search　on　encrypted　data　without　decryption　to　realize　efficient　data　utilization.　There　have　been　some　studies　on　secure　searching　over　encrypted　cloud　data,　which　pay　attention　to　both　privacy　and　practicability　of　data.　However,　most　of　them　are　based　on　accurate　keyword　matching.　The　fuzzy　keyword　search　problem　remains　unsolved.　Up　to　date,　the　existing　construction　of　fuzzy　keyword　search　schemes　has　to　build　fuzzy　keyword　set.　It　will　lead　to　tremendous　computation　and　storage　overheads.　In　this　paper,　we　propose　a　new　scheme　without　constructing　fuzzy　keyword　set.　Based　on　the　idea　of　dimension　reduction　of　Simhash,　each　keyword　is　transformed　to　a　Simhash　fingerprint　by　n　-gram　method　to　achieve　fuzzy　matching.　Combining　the　hamming　distance　and　keyword　relevance　score,　we　design　a　double　factor　ranking　algorithm　to　sort　the　results　accurately.　In　addition,　tree　structure　and　a　novel　traversal　method　are　utilized　to　further　improve　the　efficiency　of　our　proposed　scheme.　The　tree　can　be　traversed　even　if　the　value　of　the　tree　node　is　not　equal　to　the　expected　value　by　the　proposed　traversal　method.　Theoretical　analysis　and　experimental　results　show　that　the　scheme　realizes　the　ranked　fuzzy　keyword　search　over　encrypted　cloud　data.　Meanwhile,　the　computation　and　storage　overheads　are　greatly　reduced.　©　2017,　Science　Press.　All　right　reserved.