Storing　and　sharing　of　medical　data　in　the　cloud　environment,　where　computing　resources　including　storage　is　provided　by　a　third　party　service　provider,　raise　serious　concern　of　individual　privacy　for　the　adoption　of　cloud　computing　technologies.　Existing　privacy　protection　researches　can　be　classified　into　three　categories,　i.e.,　privacy　by　policy,　privacy　by　statistics,　and　privacy　by　cryptography.　However,　the　privacy　concerns　and　data　utilization　requirements　on　different　parts　of　the　medical　data　may　be　quite　different.　The　solution　for　medical　dataset　sharing　in　the　cloud　should　support　multiple　data　accessing　paradigms　with　different　privacy　strengths.　The　statistics　or　cryptography　technology　alone　cannot　enforce　the　multiple　privacy　demands,　which　blocks　their　application　in　the　real-world　cloud.　This　paper　proposes　a　practical　solution　for　privacy　preserving　medical　record　sharing　for　cloud　computing.　Based　on　the　classification　of　the　attributes　of　medical　records,　we　use　vertical　partition　of　medical　dataset　to　achieve　the　consideration　of　different　parts　of　medical　data　with　different　privacy　concerns.　It　mainly　includes　four　components,　i.e.,　(1)　vertical　data　partition　for　medical　data　publishing,　(2)　data　merging　for　medical　dataset　accessing,　(3)　integrity　checking,　and　(4)　hybrid　search　across　plaintext　and　ciphertext,　where　the　statistical　analysis　and　cryptography　are　innovatively　combined　together　to　provide　multiple　paradigms　of　balance　between　medical　data　utilization　and　privacy　protection.　A　prototype　system　for　the　large　scale　medical　data　access　and　sharing　is　implemented.　Extensive　experiments　show　the　effectiveness　of　our　proposed　solution.　(C)　2014　Elsevier　B.V.　All　rights　reserved.