see it, shake it, set it
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SEE IT, SHAKE IT, SET ITprivacy awareness and control for mobile applications
Arosha K. BandaraThe Open University, UK
Mobile East ConferenceJune 2012
RESEARCH CONTEXT
• EPSRC Funded PRiMMA Project:Privacy Rights Management for Mobile Applications
• Collaboration between The Open University and Imperial College London
• Contributions include methodologies for understanding privacy requirements, machine learning techniques, architectures for privacy aware social networks and design of real-time feedback mechanisms for privacy awareness and control.
http://primma.open.ac.uk
RESEARCH TEAM
• Bashar Nuseibeh• Yvonne Rogers• Clara Mancini• Arosha K. Bandara• Blaine Price• Lukasz Jedrejcyzk• Keerthi Thomas
• Adam Joinson
•Morris Sloman• Alessandra Russo• Emil Lupu•Naranker Dulay•Domenico Corapi• Ryan Wishart
PRIVACY THEORY
• Bi-directionality (Altmann)
• Output: sharing information with others
• Input: sensing activity of others, previous experience, etc.
StatusUpdate
Photographs
Location
12
PRIVACY THEORY
• Social translucence (Erickson and Kellog)
• Visibility
• Awareness
• Accountability
• Enforces social norms.
RESEARCH CHALLENGES
• Understand people, their behaviour and requirements.
• Translate this understanding into solutions.
RESEARCH CHALLENGES
• Understand people, their behaviour and requirements.
• Translate this understanding into solutions.
• Evaluate solutions ‘in the wild’
UNDERSTANDING PEOPLE
• Investigating mobile privacy is difficult because ...
... privacy is sensitive and depends on socio-cultural context.
... mobility introduces contextual shifts and logistical obstacles.
Centre forResearch in Computing
Mobile Facebook PracticesDr. Clara Mancini
http://primma.open.ac.uk
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UNDERSTANDING PEOPLE
• It is also difficult ...
... for people to articulate subtle concerns and preferences.
... for researchers to observe contextualised behaviour.
EXPERIENCE SAMPLING ++•We address these challenges
by combining a variety of complementary, indirect methods:
• Experience sampling enhanced with memory phrase.
• Individual, in-depth deferred contextual interviews.
EXPERIENCE SAMPLING ++•We address these challenges
by combining a variety of complementary, indirect methods:
• Experience sampling enhanced with memory phrase.
• Individual, in-depth deferred contextual interviews.
BUDDY TRACKER
Alice
Bob
1. LocationUpdates
1. Location
Updates
3. Notification2. Location Request
ContextualReal-time
LearningEngine
SEE IT: REAL-TIME FEEDBACK
• Study 1
• Two families with mixture of relationships.
• Conducted over 3 weeks, with simple real-time feedback introduced in final week.
• Quantitative data from server logs and qualitative data from ESM and post-study interviews.
Week 158%
Week 224%
Week 318%
Location Request Frequency
SEE IT: REAL-TIME FEEDBACK
• Study 2
• 3 week study with 15 participants.
• Context-aware real-time feedback with machine learning in final week.
• Quantitative data from server logs and qualitative data from ESM and post-study interviews.
Phase 142
Phase 27
Frequency of ‘intrusive’ feedback events
SEE IT: REAL-TIME FEEDBACK
0
25
50
75
100
% A
ccuracy
U7 U8 U9 U12U14 U20 U21 U22 U23 U24 U25 U30 U31 U32 U33Participant ID
Phase 1 Phase 2
Study 2 - Feedback Accuracy
PRIVACY-SHAKE
1. Initialise - vertical shake
2. Phone indicates ‘ready’
3. Set privacy - horizontal movement
- Away → Relaxed privacy settings
- Closer → Strict privacy settings
4. Privacy settings updated.
PRIVACY-SHAKE
Study 3 - User evaluation
Experience is ...
Strongly Disagree
Disagree Neutral AgreeStrongly
Agree
Enjoyable 0 2 2 7 5
Engaging 0 1 4 6 5
Pleasurable 0 2 5 5 4
Exciting 1 1 6 3 5
Fun 0 2 1 5 8
Boring 9 3 2 0 2
Frustrating 2 3 5 6 0
Annoying 2 5 5 3 1
PRIVACY-SHAKE
Study 3 - User evaluation
0
25
50
75
100
% Success
InitialiseIncrease Privacy
Reduce PrivacyPrivacy control task
Male Female
SEE IT, SHAKE IT, SET IT
• Context-aware real-time feedback supports bi-directionality and social translucence in location sharing applications.
•Machine learning techniques make awareness less intrusive, leading to greater acceptance of technology.
• Intuitive control mechanisms can be used for privacy control actions.
• Further work is required to investigate alternative privacy control interactions - e.g., multi-touch gestures.
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