The　traditional　privacy-preserving　image　retrieval　schemes　not　only　bring　large　computational　and　communication　overhead　but　also　cannot　well　protect　the　image　and　query　privacy　in　multi-user　scenarios.　To　solve　the　above　problems,　we　first　propose　a　basic　privacy-preserving　content-based　image　retrieval　(CBIR)　framework　which　significantly　reduces　storage　and　communication　overhead　compared　with　the　previous　works.　Furthermore,　we　design　a　new　efficient　key　conversion　protocol　to　support　unshared　key　multi-owner　multi-user　image　retrieval　without　losing　search　precision.　Moreover,　our　framework　supports　unbounded　attributes　and　can　trace　malicious　users　according　to　leaked　secret　keys,　which　significantly　improve　the　usability　of　multi-source　data　sharing.　Strict　security　analysis　shows　that　the　user　privacy　and　outsourced　data　security　can　be　guaranteed　during　the　image　retrieval　process,　and　the　performance　analysis　using　real-world　dataset　shows　that　the　proposed　image　retrieval　framework　is　efficient　and　feasible　for　practical　applications.　©　2019　IEEE.