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TowardsaVisualVocabularyforPrivacyConcepts
VivianGenaroMo:vmo%@gmu.edu
WashingtonDC,VASeptember21st,2016
WhatisPrivacy?
AMulFdisciplinaryConcept
• NocommonagreementsoruniversalsoluFon
Privacy…
Personal
Cultural
Legal
Technical
Contextual
…
ExisFngSoluFonsforPrivacy
TermsandCondiFons
Policies
Se%ngsNon-
DisclosureAgreements
Drawbacks
Technical
Long
Complex Notuser-centric
PrivacyinPracFce
PrivacyinPracFce
Users’MentalModels
• OnPrivacyImagery
WhoPeople,insFtuFons,
organizaFons
HowObjects,acFons,behaviors
WhyGoals,feelings,emoFons
WhereLocaFons,places
Themes
TaxonomyAcAon Analyzing,AuthenFcaFng,Blindfolding,Blocking,Blurring,
Covering,ConnecFng,Closing,Dimming,Disclosing,Erasing,Forwarding,Hiding,Localizing,Locking/Unlocking,Looking,Observing/beingobserved,Packing,ProtecFng,ProtesFng,Revealing,Sharing,Shredding,Spying,Surveilling,Synchronizing,Uploading,Uncovering
Object BlockersControlsSensorsStorage
Blinders,Curtains,Diary,Door,Fence,GateKey,Message,Padlock,Wall,WindowsSemaphoreCamera,Camcorder,MicrophoneMemoryCard,Cloud
OrganizaAon RegulatorySocialMedia&I.T.
NSA,HIPPAAAshleyMadison,Bitcoin,Facebook,Google+,Instagram,Pinterest,RSS,Twi_er,Whatsapp
People RolePublicPersonsCircle
PoliFcians,LegislatorsEdwardSnowden,GeorgeOrwellGroup,Individual
Concept Betrayal,ConfidenFality,Creepiness,Exclusivity,ConceptsFear,InFmacy,IsolaFon,Loneliness,Publicvs.Private,Safety,Secrecy,Shame
AcFonsshredding
hiding
spying
microphone
Objects
cameras
door
padlock
OrganizaFons
NSA
SocialMedia
People
Snowden
Hillary
Concepts
Solitude
IsolaFon
FrequencyofCodes
• AcFonsandobjectswerethemostfrequent– n=73andn=39
• UIdesignersfocusmainlyonacFons– Privicons,Materialicons,Mozillaicons
• Variability– Instagramwasthemostdiversesourceintermsofcodes
– Allcodeswereused
PrivacyAssurance
• Mostfrequentcodes
– RealworldacAons– Physicalobjects– Privacymechanisms
PrivacyRequirements
• Data-driven,temporalperspecFve
DatacollecFon
Datatransmission
Datastorage
Datasharing(accesscontrol)
PrivacyMetaphors
FinalRemarks
• PrivacyisamulFdisciplinaryconcept
• User-centricapproachcanhelptounderstandusers’mentalmodelsandaidtocreateprivacysoluFonsthatareeasiertouse– Bymatchingfamiliarandreal-worldconceptswithUIdesignelements
Acknowledgment• This material is based upon work supported by the NaFonal Science
FoundaFon under Grant No. 1314342. Any opinions, findings, andconclusionsor recommendaFonsexpressed in thismaterial are thoseofthe author(s) and do not necessarily reflect the views of the NaFonalScienceFoundaFon.
References• AcquisF,A.,Brandimarte,L.,&Loewenstein,G.(2015).Pri-
vacyandhumanbehaviorintheageofinformaFon.Sci-ence,347(6221),509-514.
• Balebako,R.,Leon,P.,Shay,R.,Ur,B.,Wang,Y.,&Cranor,L.(2012,May).MeasuringtheeffecFvenessofprivacytoolsforlimiFngbehavioraladverFsing.InWeb2.0Se-curityandPrivacyWorkshop.
• Caine,K.,Kisselburgh,L.G.,&Lareau,L.(2011,May).Au-diencevisualizaFoninfluencesdisclosuresinonlinesocialnetworks.InCHI'11ExtendedAbstractsonHumanFac-torsinCompuFngSystems(pp.1663-1668).ACM.
• LorrieCranor–PrivacyIllustratedWebsite.(2015)At:h_p://cups.cs.cmu.edu/privacyillustrated/
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