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SecurityandPrivacyinMobileAdvertising
HaoChen
UniversityofCalifornia,
Davis
AdsaretheFinancialPillarofMobileComputing
Mostmobilesoftwareisfree.
•Android
•Mostapps
Wheredoesrevenuecome?
•In-apppurchase
•Ads
MobileAdsEcosystem
Parties
•Users
•Appdevelopers
•Adproviders
•Advertisers
SecurityProblems
•Appdevelopers:adrevenuediversionduetocloning
•Adproviders/advertisers:adfraud
AnatomyofMobileAdTraffic
AdRevenueDiversion
Cloningharmsappecosystem
•Developers:loserevenueandincentivestomakeapps
•Markets:pollutedsearchresults
•Users:difficulttofindhighqualityapps
AdRob
Goals
Characterizeclonedapps
•Market
•Appcategory
•Adprovider
Quantifyimpactondevelopers
•Lossofadrevenue
•Lossofuserbase
Dataset:265,000appsfrom17markets
CloningbetweenMarkets
Found
•>5,000clustersofclones
•>44,000uniqueapps
CloningonEachMarket
DetermineImpact
•Naivequestion
Howmanytimeshasanappbeen
cloned?
•Betterquestion
Howmanypeopleuseaclonedapp
insteadoftheoriginal?
HowtoDetermineImpact
•Counttheusersrunningeachapp.
•Determinetheownershipofeachapp.
•Classifyoriginalvs.plagiarizedapps.
CountUsersRunningEachApp
Potentialvantagepoints
•Onthedevice
•Ontheappserver
•Onthenetwork
CountUsersRunningEachapp
Combinetrafficanalysiswithstaticanalysis
Onthenetwork
•Captureadtraffic
•ExtractclientIDs
Inthelab,foreachapp
•ExtractclientID
•Determinewhetheritisoriginalorclone
AdRob
TrafficAnalysis
•CollaboratedwithamajorUScellularprovider.
•Captured2.6billionpacketsin12days.
•Removedalluser-identifyinginformation.
LossofRevenueandUserBase
WebAdFraud
Programsthatautomatically“view”adsand“click”them
MobileAdFraud
Appsthatautomatically“view”adsand“click”them
MAdFraud
Goals
•Designsystemforautomaticallydetectingadtraffic
•Usesystemtodetectfraudandotherundesirableadbehavior
AdFraud
•Impressionfraud:requestadswheninthebackground.
•Clickfraud:clickonadswithoutuserinteraction.
MAdFraud
DynamicAnalysis
Foreachapp:
•Createanemulatorandinstalltheapp
•Runappintheforegroundfor1minute
•UseanIntenttomovetheappintothebackground
•Runappinthebackgroundfor1minute
•Captureallnetworktrafficthroughout
Neverinteractwithapptoensurealldetectedclicksarefraudulent
IdentifyImpressionsandClicks
Simpleapproach
•ReverseengineeradlibrariestofindadrequestandclickURLs
•UseURLstocountthenumberofimpressionsandclicks
Problems
•Timeintensiveforthemanyadlibraries(80+)
•Lackcontext
•Wastheadresold?
•Wastheclickproceededbyanimpression?
AutomaticallyIdentifyImpressionsandClicks
Buildrequesttrees
Identifyimpressionsusingmachinelearningbasedon
•Requesttreeproperties
•Queryparameters
•HTTPproperties
Identifyclicksbasedonrequesttreesandimpressions.
DatasetandResultsOverview
Dataset
150,000appscrawledfrom19markets
Finding:BackgroundImpressions
12,421appsmakeimpressionsinthebackground
Finding:ClickFraud
Prevention
Appcloning
•Market-scaleincrementalclonedetection
Adfraud
•Includeproofsofuserviewingorclickingprovidedbytrustedsoftware.
Conclusion
•Adsarecrucialforsustaining
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