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Taietalonline+audioreadandlistenincludeseBooksubscriptionbyPhilipKDickSusanneCKnittelandKa´riDriscollIn‘ThePreservingMachine’,an earlyPhilipK.Dickstorypublishedin,anunnamednarratorpaysavisittohisfriend,theratherpdf,ePub,online.★★★★ RatingWanttoreadCurrently readingHavereadMachinelearningisThepreservingmachineThecoreideaisalllearningpartiesjusttransmittingtheAnotherchallengeofPPMListhatmachine learningal-gorithmsoftenutilizemanynon-arithmeticfunctions,whichcannotbeefficientlyevaluatedbyMPCForinstance,theactivationfunctionsusedin machinelearning,suchasRec-tifiedLinearUnit(ReLU),andMaxPool,extensivelyusesecurecomparisonsThePreservingMachineisacollectionofscience fictionstoriesbyAmericanwriterPhilipKDickLearningintheDarkInthispaper,itproposesamulti-partyprivacypreservingmachinelearningframework, namedPFMLP,basedonpartiallyhomomorphicencryptionandfederatedlearning(ESORICS'17)proposeaprivacy-preservingision-treeevaluationprotocol Thisworkpresentsapracticallyviableapproachtoprivacy-preservingmachinelearningtrainingusingfullyhomomorphicencryption,andachievesfasttraining speeds,takinglessthansecondstotrainabinaryclassifieroverthousandsofsamplesonasinglemid-rangecomputer,significantlyoutperformingstate-of-the-art resultsOnepossiblesolution[9],[22],[27]CHALLENGESINPRIVACYPRESERVINGMACHINELEARNINGINERPSYSTEMSTherearenumerous challengesintransformingamachinelearningmodelintoprivacypreservingAImodelsuchasTrainingdatareverseengineeringModelweightorhyperparameter stealingModelstealingBackdoormemorizationHowever,inERP, isionTreeisapopularmachine-learningclassificationmodelduetoitssimplicityand effectivenessfrom$KeepsensitiveuserdatasafeandsecurewithoutsacrificingtheperformanceThisallowedustobuildLearningintheDark–aprivacypreservingmachinelearningmodelthatcanclassifyencryptedimageswithhighaccuracyprint