Trust models for mobile content-sharing applications

108 Pages·2009·1.34 MB·English

by  D. Quercia

Trust Models for Mobile Content-Sharing
Applications
Daniele Quercia
Adissertationsubmittedinpartialfulfillment
oftherequirementsforthedegreeof
DoctorofPhilosophy
ofthe
UniversityCollegeLondon.
DepartmentofComputerScience
UniversityCollegeLondon
January2009
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ForVilma(inmemory)
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I, Daniele Quercia, confirm that the work presented in this thesis is my own. Where information has
beenderivedfromothersources,Iconfirmthatthishasbeenindicatedinthethesis.
4
Abstract
UsingrecenttechnologiessuchasBluetooth,mobileuserscansharedigitalcontent(e.g.,photos,videos)
withotherusersinproximity. However,toreducethecognitiveloadonmobileusers,itisimportantthat
onlyappropriatecontentisstoredandpresentedtothem.
Thisdissertationexaminesthefeasibilityofhavingmobileusersfilteroutirrelevantcontentbyrun-
ningtrustmodels. Atrustmodelisapieceofsoftwarethatkeepstrackofwhichdevicesaretrusted(for
sendingqualitycontent)andwhicharenot. Unfortunately,existingtrustmodelsarenotfitforpurpose.
Specifically,theylacktheabilityto: (1)reasonaboutratingsotherthanbinaryratingsinaformalway;
(2) rely on the trustworthiness of stored third-party recommendations; (3) aggregate recommendations
to make accurate predictions of whom to trust; and (4) reason across categories without resorting to
ontologiesthataresharedbyallusersinthesystem.
Weovercometheseshortcomingsbydesigningandevaluatingalgorithmsandprotocolswithwhich
portable devices are able automatically to maintain information about the reputability of sources of
contentandtolearnfromeachother’srecommendations. Morespecifically,ourcontributionsare:
1. Analgorithmthatformallyreasonsongeneric(notnecessarilybinary)ratingsusingBayes’theo-
rem.
2. A set of security protocols with which devices store ratings in (local) tamper-evident tables and
areabletochecktheintegrityofthosetablesthroughagossipingprotocol.
3. An algorithm that arranges recommendations in a “Web of Trust” and that makes predictions of
trustworthinessthataremoreaccuratethanexistingapproachesbyusinggraph-basedlearning.
4. An algorithm that learns the similarity between any two categories by extracting similarities be-
tween the two categories’ ratings rather than by requiring a universal ontology. It does so auto-
maticallybyusingSingularValueDecomposition.
Wecombinethesealgorithmsandprotocolsand,usingreal-worldmobilityandsocialnetworkdata,
we evaluate the effectiveness of our proposal in allowing mobile users to select reputable sources of
content. Wefurtherexaminethefeasibilityofimplementingourproposaloncurrentmobilephonesby
examining the storage and computational overhead it entails. We conclude that our proposal is both
feasibletoimplementandperformsbetteracrossarangeofparametersthananumberofcurrentalter-
natives.
6 Abstract
Acknowledgements
IgnoranceisthefirstrequisiteoftheidealPhDstudent. InthatrespectatleastIwaseminentlyqualified
toembarkuponthisresearch. Myignorancemadedoingresearchafunexperience. ForreallyIhardly
remember“working”.Irememberonlyfeelingabsurdlypleasedwithmynonsense,forwhichIameager
tospreadsomecredits(whileofcourseremainingaccountableforallblame).
ThankstoSteveHailesandLiciaCaprawhomIamproudtocallmysupervisors.Theythoughtfully
guidedmyresearchfromnonsensetosense. ThankstoSteveforrelentlesslybullingmeintoclarifying
the purpose and execution of my research ideas. He also patiently let me disappear for many months
whileIwasworkingonmyPhD.EveryoneshouldhaveasupervisorasgenerousasSteve. Liciafirstgot
methinkingaboutapplyingtrustmodelstoportabledeviceswithherremarkablewritingsonthesubject.
Licia’sworkremainsatouchstoneforme. Shehascommentedallmypaperswithamazingtact. Herred
pen was both a mighty sword and an artist’s brush. She also weathered my minor crisis of confidence
(andamajorone). Thanks,Licia.
SpecialthanksgoestoCeciliaMascoloforalways“beinginmycorner”andforaskingmeeveryday
(fromdayone)whenmythesiswouldbedone. ThankstoUCLfolkswhosupportedthecreationofa
research blog and to Neal who was my partner in crime in creating and managing the blog. A printed
shout goes as well to the following mates who provided crucial assistance, the right fragment at the
righttime. AtUCL:Bozena,Clovis,Costin,Chris,Elias,Franco,Genaina,Ida,James,Manish,Matteo,
Mike,Piers,Stef,Socrates,andTorsten. AtNII:Eric(Platon),Eric(Tschetter),Christian,Fuyuki,Prof.
Honiden,andSooLing. AtIIIA:Andrea,Carles,Claudio,Jordi,andRonny. AtPoliTO:Laura,Paolo
andTania.
Conducting research takes money and feedbacks. Thanks to Microsoft Research Cambridge for
its financial support. Thanks to the anonymous reviewers who carefully read and commented on my
publications. Therearefewererrorsthankstoyou. Iamsoproudtobepartofthiscommunity.
I could not have asked for better friends than the following. Andre was one of the first people I
metwhenImovedtoLondon,andmyexperienceoflivinghereisinextricablefromourfriendship. In
(enchanted) Torino: Antonello, Andrea, Chiara, Enrico, and Sonia (thanks for being at the ends of a
phonewhenneeded-Iloveyouall!);andMax-Iamindebtwithhim,andheknowswhy.InBarcelona:
Antonietta, Chema and Lorenzo (thanks for your tireless talk; Lorenzo: how about dancing on tables,
sporting Aussie Bum, and drinking caipirinhas “en el chiringuito” again next year?). In Karlsruhe:
FlavioandDavidino(thanksforgenerouslysharingyoureloquenceandintellect). InTokyo: Tom(your
8 Acknowledgements
generositydefiesdescription).
Acknowledgements 9
“Itissheergoodfortunetomisssomebodylongbeforetheyleave.” ImissVilmamorethanever.
Thisthesisisforher(inmemory).
10 Acknowledgements