Ciphertext-Policy　Attribute-Based　Keyword　Search　(CP-ABKS)　facilitates　search　queries　and　supports　fine-grained　access　control　over　encrypted　data　in　the　cloud.　However,　prior　CP-ABKS　schemes　were　designed　to　support　unshared　multi-owner　setting,　and　cannot　be　directly　applied　in　the　shared　multi-owner　setting　(where　each　record　is　accredited　by　a　fixed　number　of　data　owners),　without　incurring　high　computational　and　storage　costs.　In　addition,　due　to　privacy　concerns　on　access　policies,　most　existing　schemes　are　vulnerable　to　off-line　keyword-guessing　attacks　if　the　keyword　space　is　of　polynomial　size.　Furthermore,　it　is　difficult　to　identify　malicious　users　who　leak　the　secret　keys　when　more　than　one　data　user　has　the　same　subset　of　attributes.　In　this　paper,　we　present　a　privacy-preserving　CP-ABKS　system　with　hidden　access　policy　in　Shared　Multi-owner　setting　(basic　ABKS-SM　system),　and　demonstrate　how　it　is　improved　to　support　malicious　user　tracing　(modified　ABKS-SM　system).　We　then　prove　that　the　proposed　ABKS-SM　systems　achieve　selective　security　and　resist　off-line　keyword-guessing　attack　in　the　generic　bilinear　group　model.　We　also　evaluate　their　performance　using　real-world　datasets.