TaskAssignmentinSpatialCrowdsourcing:ChallengesandApproaches

Hien ToSupervisedbyProf.CyrusShahabiDepartmentofComputerScienceUniversityofSouthernCalifornia

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ACMSIGSPATIALPhD2016

• Introduction• Ataxonomyandresearchchallenges• Privacy-preservingspatialcrowdsourcing– Risksoflocationleaks– Privacythreatsduringtaskingandreporting• TaskRabbit:acasestudy

– Privacycountermeasures:thestate-of-the-art• Conclusionandfutureworks

Outline

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SpatialCrowdsourcing(SC)

[1] http://www.gartner.com/newsroom/id/2665715

Spatialcrowdsourcing(SC):requiresworkerstophysically traveltothetask'slocationinordertoexecutethetask

Crowdsourcing:outsourcingasetoftaskstoasetofworkers.

SCApplications

Ubiquityofmobileusers

6.5billionmobilesubscriptions,93.5%oftheworldpopulation [1]

Technologyadvancesonmobiles

Smartphone'ssensors.e.g.,video cameras

Networkbandwidth

improvements

From2.5G(up to384Kbps) to3G(upto14.7Mbps)andrecently4G(upto100Mbps)

task

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SpatialCrowdsourcingApps(a.k.a MobileCrowdsourcing)

MobileCrowdsourcing:TheNextChapter,2016

TheImportanceofMobileCrowdsourcingin2015

There'sanappthatneedsyou:theriseofmobilecrowdsourcing

è TheWiley-AAGInternationalEncyclopediaofGeography4

Outlines• Introduction• Ataxonomyandresearchchallenges• Privacy-preservingspatialcrowdsourcing– Risksoflocationleaks– Privacythreatsduringtaskingandreporting• TaskRabbit:acasestudy

– Privacycountermeasures:thestate-of-the-art• Conclusionandfutureworks

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SpatialCrowdsourcingTaxonomy

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AssignmentType

Reward-based

Self-incentivised

WorkerSelected

ServerAssigned

PointTask

RegionTask

SpatialTaskType

WorkerType

ComplexTask

SpatialCrowdsourcing

PushPull

ReportType ExplicitReport

ImplicitReport

CrowdsensingCrowdsourcing

Privacy QualityControlIncentives

Reporting

Tasking

TravelcostQuality(quantity)ofassignedtasks

Communicationcost

Totalrewards

ChallengesMultipleconsiderations

Multipleobjectives

ResearchChallengesinSpatialCrowdsourcing

• Asghari etal.SIGSPATIAL2016• Bessai andCharoy ISCRAM‘16• HassanandCurryESA’16• Zhangetal.TVT’16• Gaoetal.WAIM’16• Chengetal.TKDE‘16• Tongetal.VLDB‘16• Liuetal.DASFAA‘16• Huetal.ICDE’16• Tongetal.ICDE’16• Zhangetal.WCMC‘16• Liuetal.UbiComp ‘16• Guo etal.THMS’16• Toetal.PerCom ’16

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• Toetal.TSAS’15• Alfarrarjeh etal.MDM’15• Fonteles etal.MoMM ‘15• HassanandCurry.SIGSPATIAL’15• Xiaoetal.INFOCOM’15• Xiong etal.PerCom ‘15• Pournajaf etal.ICCS‘14• HassanandCurry.UCI’14• Heetal.INFOCOM’14• Fonteles etal.SIGSPATIAL‘14• Zhangetal.UbiComp ’14• Dangetal.iiWAS ‘13• Kazemi andShahabi.SIGSPATIAL‘12

Taskassignment(orworkerselection)Processofidentifyingwhichtasksshouldbeassignedtowhichworkers

ResearchChallengesinSpatialCrowdsourcing

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Privacy-preservingSCProtectlocationsofworkersandtasks

• Toetal.TMC’16• Boutsis andKalogeraki.UbiComp‘16• Zhangetal.CN‘16• Zhangetal.ATIS‘15• Shenetal.GLOBECOM‘15• Gongetal.IoT’15• Gongetal.TETC’15• Huetal.APWeb ’15• Pournajaf etal.MDM’14,

SIGSPATIAL’15• Toetal.VLDB’14,ICDE’15• Boutsis andKalogeraki PerCom ‘13• Vuetal.INFOCOM‘12• Kazemi andShahabi SIGKDD’11

TaskschedulingWorkers’pathplanningtoperformtasks

• Wangetal.2016• Fonteles etal.JLBS‘16• Dengetal.GeoInformatica ’16• Mrazovic etal.ICDMW‘15• Chenetal.IJCAI‘15• Chenetal.AAMAS ‘15• Hadano etal.HCOMP’15• Dengetal.SIGSPATIAL’15• Chenetal.HCOMP‘14• DengandShahabi. SIGSPATIAL’13• Sadilek etal.AAAI’2013

ResearchChallengesinSpatialCrowdsourcingTrustandqualityConsiderqualityofreportdataortrustworthinessofworkers

• Liuetal.Sensor’16• Zhangetal.TETC’16• Miaoetal.DSS’16• Fanetal.SOSE’15• Anetal.HPCC’15• Kangetal.MASS’15• Cheng etal.VLDB’15• Zhaoetal.MDM’15• Wangetal.UbiComp ’15• Songetal.TVT’14• Boutsis etal.ICDCS’14• Fengetal.INFOCOM’14• Kazemi etal.SIGSPATIAL’13

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IncentivemechanismIncentivizeworkerstoperformtasks

• Zhangetal.TVT’16• Kandappu etal.CSCW‘16• Kandappu etal.UbiComp ‘16• Micholia etal.IJHCS’16• Toetal.GeoRich ’16• LiandCaoTMC’16• Guo etal.IJMHCI‘16• Thebault-Spieker etal.CSCW’15• Jin etal.MobiHoc ’15• Fanetal.ICTAI’15• Shah-Mansouri etal.ICC’15• Teodoroetal.CSCW’14• Rula etal.HotMobile ‘14• Musthag etal.CHI’13• Heimerl etal.CHI’12• Jainmes etal.PerCom ‘12• Yangetal.MobiCom ‘12• LeeandHohPMC‘10• Altetal.NordiCHI ‘10

ResearchChallengesinSpatialCrowdsourcing

Applications• KonomiandSasao Urb-IoT ‘16• Jaiman etal.UbiComp/ISWC’16• FanandTsengMOBIS‘15• KonomiandSasao UbiComp/ISWC’15• Harburg etal.CHI’15• Chenetal.SenSys ‘15• KimCHI‘15• Aubry etal.CROWDSENSING’14• Chenetal.VLDB’14• Kimetal.MMSys’14• Benouaret etal.IEEEIC’13• Coric andGruteser DCOSS’13• Koukoumidis etal.MobiSys ‘11• Goodchild andGlennon IJDE‘10

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GenericframeworksDiscusscomponents,architecture,programmingframeworkofSCapps

• Toetal.CROWDBENCH’16• Fonteles etal.RCIS‘16• Pengetal.ASE’16• Kucherbaev etal.SIGCHI’16• Sakamotoetal.COMPSAC’16• Fernandoetal.MOBIQUITOUS’13• Tamilin etal.UbiComp ‘12• Raetal.MobiSys ‘12• Yanetal.SenSys ‘09

Relatedsurveys• Pournajaf etal.SIGMODRec.‘16• Guo etal.CompSurvey‘15• ZhaoandHan2016• ChristinJSS’15

• Introduction• Ataxonomyandresearchchallenges• Privacy-preservingspatialcrowdsourcing– Risksoflocationleaks– Privacythreatsduringtaskingandreporting• TaskRabbit:acasestudy

– Privacycountermeasures:thestate-of-the-art• Conclusionandfutureworks

Outlines

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RisksofLocationLeaks

SecurityFlawInGayDatingAppGrindrRevealsPreciseLocationOf90%OfUsers

Grindr’sLocationSecurityUpdate“AnyuserwhoconnectstoGrindrinthesecountrieswillhavetheirdistancehidden automaticallybydefault,whichincludeRussia, Egypt,SaudiArabia,Nigeria,Liberia,etc.”

CouldusinggaydatingappGrindrgetyouarrestedinEgypt?

StalkersExploitCellphoneGPS“25,000adultsintheU.S.arevictimsofGPSstalkingannually, includingbycellphone.”byU.S.JusticeDepartment,Aug2010.

TheHiddenPrivacyThreatof…FlashlightApps?

“~50%topiPhones andAndroidsmartphonesdisclosed auser’s locationtothirdpartieswithoutuserconsent.”byWallStreetJournal,Dec2010.

Apple,GoogleCollectUserData

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PrivacyImplicationofLocationRelease

“InferenceAttacksonlocationtracks”[JohnKrumm,PERVASIVE'07]• GPSdatafrom172people• Findhomelocationswithmedianerrorof60meters

“Understandingindividualhumanmobilitypatterns”[Baraba´sietal.,Nature’08]

• 100,000mobilephoneusers,6months• Usermobilityà spatialprobabilitydistribution

“UniqueintheCrowd:” [Montjoye etal.,Nature’13]• 1.5millionindividuals,15months• 4 locationsuniquelyidentify95% individuals

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PrivacyImplicationofLocationRelease

• Locationleakssensitiveinformation• Politicalandreligiousview• Individual’shealthstatus• Alternativelifestyles• Affiliations

• Attacksbasedonlocations• Physicalsurveillance• Stalking• Identitytheft

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• Introduction• Ataxonomyandresearchchallenges• Privacy-preservingspatialcrowdsourcing– Risksoflocationleaks– Privacythreatsduringtaskingandreporting• TaskRabbit:acasestudy

– Privacycountermeasures:thestate-of-the-art• Conclusionandfutureworks

Outlines

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TaskRabbit:ACaseStudy[Wiki]

isanonlineandmobilemarketplacethatmatchesfreelancelaborwithlocaldemand,allowingconsumerstofindimmediatehelpwitheverydaytasks,includingcleaning,moving,delivery andhandymanwork

Leakoftasklocation duringtasking

A deliverytask

Cloakedtasklocations

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TaskRabbit:ACaseStudyLeakofworkerlocationtaskingandreporting

Cloakedtasklocations Taskstatus

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TaskRabbit:ACaseStudyLearnarequester’shomebytrackinghisrequests• Hypothesis:cloakedtaskregionscoveractualtasklocation• Validatethehypothesis:aknownlocationofanothertaskis

actuallyintheoverlappedarea

Triangulationattack

• Introduction• Ataxonomyandresearchchallenges• Privacy-preservingspatialcrowdsourcing– Risksoflocationleaks– Privacythreatsduringtaskingandreporting• TaskRabbit:acasestudy

– Privacycountermeasures:thestate-of-the-art• Conclusionandfutureworks

Outlines

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CurrentState-of-the-artCategory Paper Description

Tasking&Reporting

ShinPMC‘11 Protectingworkers’ identityandlocation (IPaddress)during task download(useTor)andreportsubmission(useanonymity service)

Reporting Boutsis PerCom ‘13• ZhangCN‘16

Workersexchange spatialtaskreportsbeforeuploadingtoSC-serversothattheservercannottellwhichworkersuploadwhichreports

Tasking Kazemi SIGKDDEx’11• VuINFOCOM‘12

SC-serverdistributesspatialtaskstoworkerssuchthateachworkerisassignedasubsetoftasksthatareclosertohimself thantoanyotherworker

ToVLDB’14• GongTETC’15• ZhangATIS‘15• ToTMC’16

SC-serverassignsaspatialtasktoasetofworkers• usedifferentialprivacytohideworkers’ locationwith

lowtravelcostandlowcommunicationoverheadwithoutcompromising assignmentsuccessrate

Pournajaf MDM’14• Hu APWeb ’15

SC-servermatches asetofspatialtaskstoasetofworkersgiventheircloaked regions• maximizetaskassignmentwhilesatisfyingtravel

budgetconstraintofeachworkerShenGLOBECOM‘15

SC-serverassignsaspatialtasktothe nearest workersontheencrypted domain

SpatialCrowdsourcingTaxonomy

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AssignmentType

Reward-based

Self-incentivised

WorkerSelected

ServerAssigned

PointTask

RegionTask

SpatialTaskType

WorkerType

ComplexTask

SpatialCrowdsourcing

PushPull

ReportType ExplicitReport

ImplicitReport

CrowdsensingCrowdsourcing

Privacy QualityControlIncentives

Reporting

Tasking

TravelcostQuality(quantity)ofassignedtasks

Communicationcost

Totalrewards

ChallengesMultipleconsiderations

Multipleobjectives

𝑡"

SC-server(Crowdsourcing

Company)t1t2t7

Requesters

SC-ServerPerformsTaskAssignment[*]

• SC-serverchoosesbestworkersfortaskbasedontask-workerproximity

• SC-serverknowsworkers’locations

𝑡#𝑡$

𝑡%

𝑡&

𝑡'

𝑡()

22[*] Kazemi and Shahabi. GeoCrowd: Enabling Query Answering with Spatial Crowdsourcing. SIGSPATIAL 2012

WhyDifferentialPrivacy [*]?

Privacyguaranteesü Protectionforindividualsü Protection againstbackgroundknowledgeü Strongtheoreticalguaranteesonprivacyofreleaseddata

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Differentialprivacysupportsvariousaggregationqueries,e.g.,count,min,max,mean,etc.

PrivatizedResults

PrivatizedAnalysisDatabase

𝑅𝐷 𝑄(𝐷) = 𝑅

[*] Dwork, Nissim, McSherry, Smith, Calibrating Noise to Sensitivity in Private Data Analysis 2006

AdoptionofDifferentialPrivacy

“iOS10addsSiriintelligenceintoQuickType andPhotos,…,andopensupSiri,Maps,PhoneandMessagestodevelopers—whileincreasingsecurityand privacy withpowerfultechnologieslikeDifferential Privacy.”CraigFederighi, Apple’sseniorvicepresidentofSoftwareEngineering,June13,2016.

“RAPPOR enables learning statistics about the behavior of users’ softwarewhile guaranteeing client privacy. The guarantees of differential privacy,which are widely accepted as being the strongest form of privacy, ….RAPPOR introduces a practical method to achieve those guarantees.” ÚlfarErlingsson, Google’s Tech Lead Manager, Security Research

AppleandGooglehaveadaptedDPtodiscoverusagepatternsfromalargenumberofusers.

DifferentiallyPrivatePublicationofLocationEntropyThursday,November3.8:00- 9:00AM(Session11)

DifferentialPrivacyinUse

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OutputofQ:5+symmetricrandomLaplacenoise

Inspatialcrowdsourcing,𝑄 = “Howmanypeopleinaparticulararea?”

UsingDifferentialPrivacyinTaskAssignmentphaseofSpatialCrowdsourcingtohidethelocationofworkerswithlowcost andlowoverheadwithoutcompromisingperformance.

ProblemStatement

• Lowcost:travelcost• Lowoverhead: communicationoverheadrequiredtosendtaskrequeststoworkers

• Performance:#ofperformedtasks

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Privacy-PreservingTaskAssignmentPerformtaskassignmentinDP-compliantmanner• UseworkerdatasetPrivateSpatialDecomposition(PSD)

Challenges:1. DPintroduces“fake”workers- mayleadto

inefficientassignment• Assigneachtasktoallworkersisnotscalable

• Ensuretaskcompletion,butkeepoverheadlow,e.g.,minimizethenumberofworkersthatneedtobenotified

2. Communicationmodelsignificantlycomplicated• EstablishingdirectcommunicationchannelsviolatesDP!

• Instead,disseminatetaskrequestswithingeocast region[*]

[*] Navas and Imielinski. Geocast: geographic addressing and routing, MOBICOM’97 27

0 3 3 2

4 7 6 3

4 5 2 3 1

2 2 23 6

3 3 2

1.CSPaggregatelocations

3.SC-serverreceivestaskrequest

4.SC-serverqueriesPSDtofindgeocast region(GR)thatenclosessufficient workers

5.SC-servergeocast thetasktoallworkerswithinGR

2.CSPreleasesPSD,accordingtoDP

SystemArchitecture

Aggregateslocations

CellServiceProvider

SC-serverSanitizeslocations

Consent

Geocast[*]

PSD

Workers

[*] Navas and Imielinski. Geocast: geographic addressing and routing, MOBICOM’9728

PerformanceMetricsandResults

AssignmentSuccessRate(ASR)• Ratiooftasksacceptedbyaworker

WorkerTravelDistance(WTD)• Captures travelcostorassignmentquality

AverageNotifiedWorkers (ANW)• Capturesoverhead(communicationrequiredto

geocast taskrequestsorcomputationofassignmentalgorithm)

29150% increasecomparedtonon-privatecase

20% increasecompared tonon-privatecase

Similarperformance compared tonon-privatecase

PublishingResults

[Toetal.TMC2016] [2]

• Protectingworkerlocationsacrossmultipletimestamps

[Toetal.VLDB2014]• Differentially-privateframeworkfortaskassignment

[Toetl al.ICDE2015] [1]• Toolboxforturningspatialcrowdsourcingparameters

[1] To et al. PrivGeoCrowd: A Toolbox for Studying Private Spatial Crowdsourcing, ICDE 2015[2] To et al. Differentially Private Location Protection for Worker Datasets in Spatial Crowdsourcing, TMC 201630

• Introduction• Ataxonomyandresearchchallenges• Privacy-preservingspatialcrowdsourcing– Risksoflocationleaks– Privacythreatsduringtaskingandreporting• TaskRabbit:acasestudy

– Privacycountermeasures:thestate-of-the-art• Conclusionandfutureworks

Outlines

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• Taxonomyofspatialcrowdsourcing• Moststudiesfocusontaskassignmentproblem– Multipleobjectives:number(quality)ofassignedtasks,totalrewards,travelcost,communicationoverhead,etc.

– Multipleconsiderations:privacy,trust,quality,incentive

• Privacyissue– Privacyrisksoccurtoworkers andrequestersduringtaskingandreportingphases

– Varioustechniqueshavebeenused:pseudonymity,cloaking,perturbation,encryption,exchange-based

• Taskassignmentwithrigorousprivacyprotection– Thecostofprivacyispractical– Butnonesolvesprivacyrisksforbothworkersandtasks

Conclusionsandfutureworks

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Q/AHienTo

Email:hto@usc.edu

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