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Users Can Deduce Sensitive Locations

Protected by Privacy Zones on Fitness Tracking Apps

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Jaron Mink, Amanda Rose Yuile, Uma Pal, Adam J Aviv, Adam Bates

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Allows users to record exercises such as runs and bike rides

  • Often includes map of the exercise route

Can be shared with other app users and on social media

Fitness tracking applications

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Theft1

Physical Safety2

[1] Philippe Tremblay. 2018. Thieves allegedly use Strava to identify and steal cyclist’s $21,000 bike collection. tinyurl.com/2p8pje89

[2] Olivia Nuzzi. 2020. What It’s Like to Get Doxed for Taking a Bike Ride. https://tinyurl.com/2p828z39

Fitness apps pose privacy risks

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Privacy Zone (PZ)

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Technically Skilled User

(Hassan et al.

USENIX 2018)

Typical User

(This work)

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RQ1: What are users’ general perceptions and behaviors regarding privacy when using fitness apps?

RQ2: How effective are privacy zones at protecting users’ sensitive locations against other users?

RQ3: How do users perceive the utility and effectiveness of privacy zones?

Research questions

Pre-Task Survey

Privacy Zone Task

Post-Task Survey

Pre-Task Survey

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RQ1: What are users’ general perceptions and behaviors regarding privacy when using fitness apps?

RQ2: How effective are privacy zones at protecting users’ sensitive locations against other users?

RQ3: How do users perceive the utility and effectiveness of privacy zones?

Pre-Task Survey

Privacy Zone Task

Post-Task Survey

Research questions

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3. Place Pin

2. Place PZ

1. Select PZ Size

Dependent Variable (Guess Error):

- 12 measurements per participant

- distance(True Center, Inferred Center)

Treatments:

- Number of Routes: (1 v 3 routes)

- Size of Privacy Zone: (1/8th, 3/8th, 5/8th mi)

Pre-Task Survey

Privacy Zone Task

Post-Task Survey

Methodology: inference task

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Privacy Zone Task

Post-Task Survey

More routes and smaller radii decrease guess error

Pre-Task Survey

3-Route is smaller than 1-Route

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Privacy Zone Task

Post-Task Survey

More routes and smaller radii decrease guess error

Pre-Task Survey

1/8th mi is smaller than 5/8th mi

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Privacy Zone Task

Post-Task Survey

More routes and smaller radii decrease guess error

Pre-Task Survey

User 3-Route success rate: 63%

User 1-Route success rate: 25%

Algorithm 3-Route success rate: 97%

The relation between

1/8th and 5/8th is smaller

in 3-Route than in

1-Route

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Privacy Zone Efficacy

Future Privacy Preference

Privacy Zone Task

Privacy Zone Usability

  • Eleven likert-scale/open-ended questions

Methodology: privacy zone perceptions

Post-Task Survey

Pre-Task Survey

  • Does not impede user experience

        • ~70%: very little or no negative impact

        • 67% would use PZ in future

        • 90% PZ used alongside another privacy mechanism

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Attacker-Perspective

“How often do you think that you were correct when identifying the location with the pin?”

Defender-Perspective

“Based on your experiences with this task, how effective are Privacy Zones at protecting sensitive locations?”

66% (1 route) ~= 63% (3 route)

43% (1 route) <* 63% (3 routes)

Privacy Zone Task

Post-Task Survey

Pre-Task Survey

All:

By Route:

48%: Somewhat or very often

65%: Somewhat or very confident

PZ efficacy depends on perspective and task condition

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Recommendations for:

Privacy Features

Users

Fitness Tracking

Applications

Investigate new defenses according to inference strategies and unaddressed concerns

Better inform users of

risks and privacy methods

Better protect user privacy given inference strategies and other user protection strategies

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Prior Perceptions & Behavior: (see paper for details)

Efficacy of privacy zones:

  • More routes and smaller privacy zones improve inference
  • Users are successful at finding locations

Perceptions of privacy zones:

  • Users are largely accepting of privacy zones
  • Perceived benefit in use alongside other mechanisms

Takeaways

Jaron Mink

Amanda Rose Yuile

Uma Pal

Adam J. Aviv

Adam Bates