locality and privacy in people-nearby applications

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Locality and Privacy in People-Nearby Applications Mike Lin UbiComp’13, September 8–12, 2013, Zurich, Switzerland

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Locality and Privacy in People-Nearby Applications. UbiComp’13, September 8–12, 2013, Zurich, Switzerland. Mike Lin. Outline. Authors Introduction Related works People-Nearby Applications Methodology Discussion Comment. Authors. Eran Toch - PowerPoint PPT Presentation

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Page 1: Locality and Privacy in  People-Nearby Applications

Locality and Privacy in People-Nearby Applications

Mike LinUbiComp’13, September 8–12, 2013, Zurich, Switzerland

Page 2: Locality and Privacy in  People-Nearby Applications

Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

Page 3: Locality and Privacy in  People-Nearby Applications

Authors

Eran TochLecturerDepartment of Industrial Engineering, The Iby and Aladar Fleischman Faculty of Engineering , Tel Aviv University.

Page 4: Locality and Privacy in  People-Nearby Applications

Authors

Lab and Research Group at Tel Aviv UniversityJunior Faculty - Cognitive Aspects of Human Factors, Quantitative Models of Human Performance at Tel Aviv University

Project Manager & Inter-Enterprise Process Management System Designer at IBMSecurity Staff at IAA

Page 5: Locality and Privacy in  People-Nearby Applications

Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

Page 6: Locality and Privacy in  People-Nearby Applications

Introduction

People-Nearby Applications (PNAs)•For dating

•Grindr or Skout•For finding activity partners

•Highlight or Circle

Page 7: Locality and Privacy in  People-Nearby Applications

Introduction

People-Nearby Applications (PNAs)•For dating

•Grindr or Skout•For finding activity partners

•Highlight or Circle

Page 8: Locality and Privacy in  People-Nearby Applications

Introduction

People-Nearby Applications (PNAs)•For dating

•Grindr or Skout•For finding activity partners

•Highlight or Circle

Page 9: Locality and Privacy in  People-Nearby Applications

Introduction

Badoo•175 million users

Skout •1 million new users every month

Grindr•4.1 million registered users

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Introduction

•Two main contributions •Analysis of usage patterns•Connection of the physical realm and the digital realm

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Introduction

• Circlehttp://www.youtube.com/watch?v=WYTT3FoKrMo

• SayHihttp://www.youtube.com/watch?v=utAfdLVByLI

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Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

Page 13: Locality and Privacy in  People-Nearby Applications

RELATED WORKS

• Privacy in location-based social applications•Foursquare

•empirically explore emerging usage practices in the real world.

Page 14: Locality and Privacy in  People-Nearby Applications

RELATED WORKS

• computer-mediated communication• certain language-based strategies to reduce uncertainty

Page 15: Locality and Privacy in  People-Nearby Applications

RELATED WORKS

• Hybrid ecology• Dragon Quest 9

• interact with each other in an urban environment

Page 16: Locality and Privacy in  People-Nearby Applications

Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

Page 17: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

Focus•provide general means of communication between strangers

Page 18: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Badoo is a social network where you can meet new people.•Email, name, age,gender, sexual orientation

Page 19: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Banjo integrates the largest social networks to provide on-the-ground view.•Facebook login

Page 20: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Blendr -The new way to make friends nearby.•Birth date

Page 21: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Circle Social Radar to find your friends and contacts that are nearby.•Facebook login

Page 22: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Highlight -Fun, simple way to learn more about the people around you.•Facebook login

Page 23: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Grindr Grindr is the essential location-based app to meet gay, bi and curious guys for dating, socializing and friendship.•Nickname

Page 24: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•SayHi SayHi can help you find new people nearby! •Nickname, sexual orientation, birthdate

Page 25: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

•Skout Instantly meet people near you or around theworld.•Sexual orientation,search radius

Page 26: Locality and Privacy in  People-Nearby Applications

PEOPLE-NEARBY APPLICATIONS

Page 27: Locality and Privacy in  People-Nearby Applications

Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

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METHODOLOGY

•100 KM or less from the interviewer.

•320 users were invited

•Interviewed 25 participants.

Page 29: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Why do participants use the applications?

Page 30: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

’talking with new people’,’dating’, and ’making new Friends’

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METHODOLOGY

Use of Location

”Of course that location is important. I want to find someone and meet her, so why should I waste time on just talking? I won’t talk with someone who is 200 kilometer away.” -Male

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METHODOLOGY

Use of Location

I am here to meet people from Asia. I am interestedin the Far East.”-Female

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METHODOLOGY

Use of Location

”I am here mainly to improve my English.”-Male

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METHODOLOGY

Use of Location

”the location does tell me a little about them, their culture, their perception.” -Female

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METHODOLOGY

Trust Approaches

“nothing can help me trust people in this application”-Female

Page 36: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust Approaches

“is not particularly safe”-Female

Page 37: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust Approaches

“I do not believe that you can find someone who can be trusted through this app”.-Female

Page 38: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust Approaches

“Deception is very easy. Everybody can fill in fake details into their profiles.”- Male

Page 39: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust Approaches

“Everybody wears a mask when they are online”-Female

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METHODOLOGY

Trust Approaches

“Everything seems to be fake here. I do not think that I will be ablento meet someone here... I do not trust these apps very much.” -Male

Page 41: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust Mechanisms

location, profile, chat and blocking.

Page 42: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust Mechanisms

“Knowing the distance kind of helps me trust people.The feeling is that you can trust someone nearby as he or she are not total strangers.”-Male

Page 43: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust MechanismsQuestion: Does location helps you trust other people?Answer: -Male

Yes, in a sense. Also, because they see where I am. If I am saying that I am somewhere near X and they see that its really so.On the other hand, its also possible to use [location] for deception by blocking it on the mobile.

.-Male

Page 44: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Trust MechanismsQuestion: does the physical location [of the otherperson] affect your trust?Answer: -FemaleYes. The further away I am, the more I believe there is no chance of meeting that person.

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METHODOLOGY

Trust Mechanisms

“I try to ask a lot of questions, and to request photos to see if the person is trustworthy or not.”-Male

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METHODOLOGY

Trust Mechanisms

“A profile picture and a picture album mean that theperson is actually the person in the picture... Posts, vocabulary and location give an indication for intelligence and trust.”-Male

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METHODOLOGY

Trust Mechanisms

“I ask some basic questions, and I continue to where it takes me. If I see that it [the chat] becomes harassing,I block right away.”-Female

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METHODOLOGY

Privacy Management

•Recognizable picture•only 3 out of the 7 females exhibiting

•“I never give my [phone] number here or my Facebook [page].”-Female

Page 49: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Application Usage Context

Page 50: Locality and Privacy in  People-Nearby Applications

METHODOLOGY

Application Usage Context“I move them to Skype, with camera and all that.”-

Female

“Question: How do you make sure that someone is trustful?

Answer: -MaleFacebook. You cannot fake pictures with friends,and

friends’ comments and stuff like that.”

Page 51: Locality and Privacy in  People-Nearby Applications

Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

Page 52: Locality and Privacy in  People-Nearby Applications

DISCUSSION

•Pseudo-anonymized identity schema•Public-hybrid ecology•Search radius:

•Average of 50km,Standard deviation of 20km.

Page 53: Locality and Privacy in  People-Nearby Applications

Outline

AuthorsIntroductionRelated worksPeople-Nearby ApplicationsMethodologyDiscussionComment

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COMMENT

Mark Zuckerberg -This is a map of all of the friendships formed on Facebook across the world. 2013/9/24

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COMMENT

Radius:90km