Computation　outsourcing　using　virtual　environment　is　getting　more　and　more　prevalent　in　cloud　computing,　which　several　parties　want　to　run　a　joint　application　and　preserves　the　privacy　of　input　data　in　secure　computation　protocols.　However,　it　is　still　a　challenging　task　to　improve　the　efficiency　and　speed　of　secure　floating　point　calculations　in　computation　outsourcing,　which　has　efficient　secure　integer　calculations.　Therefore,　in　this　paper,　we　propose　a　framework　built-up　with　a　privacy-preserving　computation　toolkit　with　floating-point　numbers　(FPN),　called　PCTF.　To　achieve　the　above　goal,　we　provide　efficient　toolkit　to　ensure　their　own　data　that　FPN　operations　can　be　securely　handled　by　homomorphic　encryption　algorithm.　Moreover,　we　provide　simulation　results　to　experimentally　evaluate　the　performance　of　the　accuracy　and　the　efficiency　of　PCTF,　which　will　slowdown　with　10x　time　consumption　per　in　the　secure　floating-point　addition　and　secure　floating-point　multiplication.　Existing　FPN　division　is　constantly　approaching　result　of　division,　or　obtaining　the　quotient　and　remainder　of　division,　in　terms　of　precision,　it　is　impossible　to　guarantee　the　precise　range　stably.　However,　our　PCTF　has　higher　precision　in　secure　floating-point　division,　and　the　precision　can　be　guaranteed　at　least　10-　17.　©　2021,　ICST　Institute　for　Computer　Sciences,　Social　Informatics　and　Telecommunications　Engineering.