0cdc-mrf-anomaly

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1、1AnomalyDetectioninSensorNetworksbasedonLargeDeviationsofMarkovChainModelsIoannisCh.PaschalidisyYinChenzAbstract—Weintroduceananomalydetectionframeworkforwhichprecludestheuseofsophisticatedsecuritymeasures,wirelesssensornetworksabletodetectstatisticall

2、ysignicantWSNETsareextremelyvulnerabletoawiderangeoftemporalorspatialchangesineithertheunderlyingprocesstheadversarialattacks,exploits,viruses,andotherinformationsensornetworkismonitoringorthenetworkoperationitself.securityvulnerabilities[2].Followinga

3、computersystemsWeconsideraseriesofMarkovmodelstocharacterizethebehaviorofthesensornetwork,includingtree-indexedMarkovapproach,mostoftheliteraturehasonlyconsideredprotocolchainswhichcanmodelitsspatialstructure.Largedeviationsdesignasawaytoaddressthesesec

4、urityconcerns.techniquesareusedtocomparethedistributionoftheMarkovOurworkconsidersanomalydetectioningeneralenoughmodelestimatedfrompastanomaly-freetraceswithitsmosttermsthatcanaccommodateboththemonitoringandnet-recentempiricalmeasure.Wedevelopoptimaldec

5、isionrulesworksecurityrelatedproblemsoutlinedabove.WedeneforeachcorrespondingMarkovmodeltoidentifyanomaliesinrecentactivity.Simulationresultsvalidatetheeffectivenessofthenotionofa“state”associatedwithanodeofthenetworktheproposedanomalydetectionalgorith

6、ms.andassumethatitsevolutionisMarkovian.Weconsideraseriesofmodelsthatcanmodeltheevolutionofthestatebothintimeandinspace,thelatterusingtheconnectivityI.INTRODUCTIONmodelofthenetwork.WepayparticularattentiontotreesWirelessSensorNETworks(WSNETs)arenetworks

7、ofwhichisacommonconnectivitystructureforWSNETs.oftensmalldevicesthatcommunicatewirelleslyandareusedThekeytechnicaltoolweuseislargedeviationsfortomonitor(andcontrol)aphysicalsystem.WSNETnodesMarkovchainsdevelopedin[3,4].Largedeviationstheorycanbepoweredb

8、ybatteriesandhavelimitedprocessingprovidesapowerfulwayofhandlingrareeventsandtheiras-andstorageabilities.Coupledwithappropriatesoftwaresociatedprobabilities.Assumingthatweknowthetransition(protocols)theycanself-conguretoformanet