Data-Driven Privacy Indicators Hamza Harkous , Rameez Rahman, Karl - - PowerPoint PPT Presentation

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Data-Driven Privacy Indicators Hamza Harkous , Rameez Rahman, Karl - - PowerPoint PPT Presentation

Jan 03, 2023 333 likes •856 views

Data-Driven Privacy Indicators Hamza Harkous , Rameez Rahman, Karl Aberer EPFL, Switzerland Workshop on Privacy Indicators, SOUPS 2016 Permissions in 3rd Party Apps Facebook Android 2 Permissions in 3rd Party Apps 11/26/2015 Request for

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Data-Driven

Hamza Harkous, Rameez Rahman, Karl Aberer

Privacy Indicators

EPFL, Switzerland

Workshop on Privacy Indicators, SOUPS 2016
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Permissions in 3rd Party Apps

Android Facebook

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Permissions in 3rd Party Apps

Dropbox

11/26/2015 Request for Permission https://accounts.google.com/o/oauth2/auth?client_id=372897164722-ssp2tb8m4sgvhn2s15jtt8dtuhtocbsi.apps.googleusercontent.com&scope=https%3A%2F%2… 1/1 Allow Deny Pdf Merger would like to: View and manage Google Drive files and folders that you have opened or created with this app View and manage the files in your Google Drive By clicking Allow, you allow this app and Google to use your information in accordance with their respective terms of service and privacy policies. You can change this and other Account Permissions at any time.

Google Drive

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Permissions in 3rd Party Apps

Dropbox

Allow Deny Pdf Merger would like to: View and manage Google Drive files and folders that you have opened or created with this app View and manage the files in your Google Drive By clicking Allow, you allow this app and Google to use your information in accordance with their respective terms of service and privacy policies. You can change this and other Account Permissions at any time.

Google Drive

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Permissions in 3rd Party Apps

Dropbox

Allow Deny Pdf Merger would like to: View and manage Google Drive files and folders that you have opened or created with this app View and manage the files in your Google Drive By clicking Allow, you allow this app and Google to use your information in accordance with their respective terms of service and privacy policies. You can change this and other Account Permissions at any time.

Google Drive

Challenges

One size fits all Habituation effects Different from user expectations

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Data-Driven Privacy Indicators (DDPIS)

Dynamic indicators as a function of users’ data

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Data-Driven Privacy Indicators (DDPIS)

Dynamic indicators as a function of users’ data

Service provider delivers insights that help users make privacy-aware decisions.

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Focus on 3rd Party Cloud Apps

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Your Files

CSPs 3rd party apps Files

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Problem 1: Dealing with App Over-privilege

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Dealing with App Over-privilege

64%

  • f 3rd party apps request

more data than needed*

*H. Harkous, R. Rahman, B. Karlas, and K. Aberer. "The Curious Case of the PDF Converter that Likes Mozart: Dissecting and Mitigating the Privacy Risk of Personal Cloud Apps", PoPETs
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ZIP Extractor wants to:

Current Interface

View your basic profile info View your email address View and manage Google Drive files and folders that you have opened or created with this app. View the files in your Google Drive

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per-file access full access

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ZIP Extractor wants to:

View your basic profile info View your email address View and manage Google Drive files and folders that you have opened or created with this app. View the files in your Google Drive

  • btain permissions it needs to function
  • btain permissions it doesn't need
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ZIP Extractor wants to:

View your basic profile info View your email address View and manage Google Drive files and folders that you have opened or created with this app. View the files in your Google Drive

  • btain permissions it needs to function
  • btain permissions it doesn't need

Labelling

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SLIDE 15 10 privyseal.epfl.ch
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Immediate Insights (examples) from your Data 1- Immediate Insights

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SLIDE 17 11 They tell the app that you have the below image, named ‘brithday21.jpg':

2- Immediate Insights 1- Immediate Insights

privyseal.epfl.ch
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SLIDE 18 12 They tell the app that you have an image, named ‘dinner.jpg’ , which was captured at this location:

2- Immediate Insights 1- Immediate Insights

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Far-reaching Insights from your Data 2- Far-reaching Insights

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Far-reaching Insights from your Data 2- Far-reaching Insights

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…with Entities/Concepts/Topics 3- Far-reaching Insights 2- Far-reaching Insights

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…Sentiments 3- Far-reaching Insights 2- Far-reaching Insights

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…Top Collaborators 3- Far-reaching Insights 2- Far-reaching Insights

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…Shared Interests 3- Far-reaching Insights 2- Far-reaching Insights

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3- Far-reaching Insights …Faces with Context 2- Far-reaching Insights

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3- Far-reaching Insights …Faces on Map 2- Far-reaching Insights

privyseal.epfl.ch
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Inefficacy of Baseline Permissions

16% 23% 39% Baseline Immediate Far-reaching

Acceptance Likelihood

(Percentage of users who would still accept over-privileged apps)

  • Online experiment
  • Actual user’s data
  • 160 participants in 3 groups
  • GLMMs for significance tests
*H. Harkous, R. Rahman, B. Karlas, and K. Aberer. "The Curious Case of the PDF Converter that Likes Mozart: Dissecting and Mitigating the Privacy Risk of Personal Cloud Apps", PoPETs
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The Power of Relational Insights

<

They tell the app that you have the below image, named ‘brithday21.jpg':

Acceptance Likelihood

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Impact of Face Recognition

<

Acceptance Likelihood

8% 21%

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Problem 2: Minimizing Interdependent Privacy

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SLIDE 31 Company 1 Company 2 Company 3 Company 4 Company 5 Company 6 24
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SLIDE 32 Company 1 Company 2 Company 3 Company 4 Company 5 Company 6

Too Many Shareholders → Larger Attack Surface

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Company 1 Company 2 Company 3

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Company 1 Company 2 Company 3

Fewer Shareholders → Better Privacy

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History-based Insights

Keep data with a minimum number of vendors When possible, install apps from vendors that already have access to your data, either directly or from collaborators.

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Baseline Permission Model

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History-based (HB) Insights Model

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Findings

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Superiority of the HB Insights

75-84% 42-56% Baseline History-based

(Percentage of users who would favor the app with existing access to their data)

  • Online experiment (CrowdFlower)
  • Role-playing scenario
  • 141 participants in 2 groups
  • Fisher’s test for significance
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User Motivations

cross-app compatibility interface familiarity satisfaction with the previous vendor

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User Motivations

cross-app compatibility interface familiarity satisfaction with the previous vendor

Users’ data can be used to highlight the other advantages of taking privacy-aware decisions

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Further Applications of DDPIs

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Extensions of FR and HB Insights

mobile/social networking platforms browser extensions (visualize browser history contents) visualize the power of 4th party ad providers

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New DDPIs

consequences of privacy settings how others view my encrypted data visualize which of the user’s apps still operate with encryption

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Post-installation Scenario

insights based on downloaded files insights based on accessed location*

* H. Almuhimedi, F. Schaub, N. Sadeh, I. Adjerid, A. Acquisti, J. Gluck, L. F. Cranor, and Y. Agarwal. Your location has been shared 5,398 times!: A field study on mobile app privacy nudging. CHI 2015
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Limitations

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The Business Case

The provider is interested in strengthening the ecosystem Could privacy be the selling point?

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The Economic Cost

extra computational cost data analysis already run for other purposes (e.g. search)

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Usability Challenges

How to stay minimize information overload? How to prioritize messages when multiple optimizations are possible?

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DDPIS Privacy Assistants

What’s Next?

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Questions/Feedback?

hamza.harkous@gmail.com hamzaharkous.com

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Image/Media Credits

Markus Magnusson: slide 8 David Holm: slide 24 Freepik: slide 23 Fab Design: slide 41