Exam Answers From Machine Learning Course

MathematicalmodelsforIoTMuxtorovAbdulazizT ashkent,Uzbekistana.muxtorov@newuu.uzAbstractDeeplearningandothermachinelearningappr oachesar edeployedtomanysystemsr elatedtoInternetofThingsorIoT .However ,itfaceschallengesthatadversariescantakeloopholestohackthesesystemsthr oughtamperinghistorydata.Thispaperfirstpr esentsoverallpointsofadversarialmachinelearning.Then,weillustratetraditionalmethods,suchasPetriNetcannotsolvethisnewquestionefficiently .Afterthat,thispaperusestheexamplefr omtriage(filter)analysisfr omIoTcybersecurityoperationscenter .Filteranalysisplaysasignificantr oleinIoTcyberoperations.Theoverwhelmingdatafloodisobviouslyabovethecyberanalyst sanalyticalr easoning.T ohelpIoTdataanalysismor eefficient,wepr oposear etrievalmethodbasedondeeplearning(r ecurr entneuralnetwork).Besides,thispaperpr esentsar esear chondatar etrievalsolutiontoavoidhackingbyadversariesinthefieldsofadversarymachineleaning.Itfurtherdir ectsthenewappr oachesintermsofhowtoimplementingthisframeworkinIoTsettingsbasedonadversarialdeeplearning.KeywordsDeepLearning,AdversarialMachineLearning,MachineLearning,InternetofThings,IoTI .IN TR O DUCTIO NM ach in el e arn in g,e sp ecia llyD eepL earn in g,i si n cre asin glyp opula rn oto nlyi nd ailyl if e ,b uta ls oi nm an ys c ie n ced is c ip lin es,i n clu din gI n te rn eto fT hin gso rI o T [1 ].F ore x am ple ,c o m pute rs e cu rityi nt e rm so fI o Tn etw orki n tr u sio nsd ete ctio n,a n dm alw arei d en tif ic atio nr e lie so na u to m atica p pro ach ess te m min gf ro md eepl e arn in g,b utt h osea reo nlyt w oe x am ple so fd eepl e arn in gi nI o Ts e cu rity .W here as,d eepl e arn in gi se ff e ctiv ea ta v era g en orm alc ase s,s u