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1、OntheModelingofHonestPlayersinReputationSystemsQingZhangTingYuDepartmentofComputerScienceDepartmentofComputerScienceNorthCarolinaStateUniversityNorthCarolinaStateUniversityAbstractholdsinadecentralizedsystem.Manytrustfunctionshavebeenproposedintheliterature
2、Theeffectivenessofreputation-basedtrustmanagement(e.g.,[5,8,9,11–13].Buttheyoftencanbeeasilymanipu-fundamentallyreliesontheassumptionthatanentitysfu-latedbyadversaries.Wearguethattheessentialreasonforturebehaviormaybepredictedbasedonitspastbehav-thisinsuffic
3、iencyresidesinthefactthatadversariesdonotior.Thoughmanyreputation-basedtrustschemeshavebeenfollowtheabovementionedassumption.Theydonotactproposed,theycanoftenbeeasilyexploited,asanattackerconsistently.Instead,theymayintentionallyadapttheirbe-mayadaptitsbeha
4、viorandmaketheaboveassumptionin-haviortotakeadvantageofatrustfunction.Existingtrustvalid.Inthispaper,webuildastatisticmodelforhonestfunctionsaresuitabletoassessthetrustworthinessofenti-entitiesindecentralizedsystems,whichservesasaprofil-tieswhobehaveconsiste
5、ntly,butarevulnerabletoadver-ingtooltoidentifysuspiciousentities.Itcanbecombinedsarieswhomaychangetheirbehaviorarbitrarily.withexistingtrustschemestoensurethattheyareappliedInthispaper,insteadofdesigningyet-anothertrustfunc-toentitieswhosetransactionrecords
6、areconsistentwiththetionandapplyingitindistinguishablytoallpartiesinasys-statisticmodel.Thisapproachlimitsthemanipulationca-tem,weadvocateatwo-phaseapproachtotrustassessment.pabilityofadversaries,andthuscangreatlyimprovetheThisapproachintegratesthemodelingo
7、f“honestplayers”qualityofreputation-basedtrustassessment.withtrustfunctions.By“honestplayers”,wemeanthoseentitieswhobehaveconsistentlyinasystem.Inthefirstphaseofourapproach,weexaminethetransactionhistory1Introductionofanentity.Onlywhenitfollowsthemodelofhone
8、stplayers,willweapplytrustfunctionstofurtherdetermineitstrustworthinessinthesecondphase.ThosewhodonotReputationmechanismsareoneofthemajortechniquespassthefirstphasemaybeeitherdiscardedasuntrustwor-fores
