Symposium On Usable Privacy and Security
2nd Annual Privacy Personas and Segmentation (
- Opening Keynote Privacy Personae – US Legal (and Political) Considerations.
- A. Michael Froomkin
- Implications of Device Sharing Behaviors for Predicting Privacy Preferences.
- Anna Turner, Tara Matthews, Kerwell Liao, Marianne Berkovich, and Sunny Consolvo
- Privacy and Behavioral Advertising: Towards Meeting Users‘ Preferences.
- Pedro Giovanni Leon, Ashwini Rao, Florian Schaub, Abigail Marsh, Lorrie Faith Cranor and Norman Sadeh
- Perceived Frequency of Advertising Practices.
- Sai Teja Peddinti, Allen Collins, Aaron Sedley, Nina Taft, Anna Turner and Allison Woodruff
- Location-Based Applications – Benefits, Risks, and Concerns as Usage Predictors.
- Maija Poikela, Ina Wechsung and Sebastian Möller
- Multiple Facets of Information Privacy: A Socio-Cultural Approach.
- Hsiao-Ying Huang and Masooda Bashir
- Cross-Cultural Privacy Prediction.
- Yao Li, Bart P. Knijnenburg, Alfred Kobsa and M-H. Carolyn Nguyen
- Balancing Privacy Concerns and Impression Management Strategies on Facebook.
- Jessica Vitak
- Lightning Talks
- Closing Keynote Learning People's Privacy Preferences: Opportunities and Challenges.
- Norman Sadeh
Please note: Authors will be given a maximum of 18 minutes to present their papers, plus time for questions and discussion. Time limits will be rigorously enforced throughout the day by session chairs.
Scope and Focus
Scholars and practitioners have long been interested in understanding and measuring privacy attitudes and concerns, and their relationship with privacy behavior. Over time, an awareness has emerged of the importance of context in privacy concerns, and the complex relationship between concerns and actual behaviors. In recent years, proposals have been made to segment individuals into more granular and detailed categories of privacy concerns or behaviors, and classifying or predicting their privacy types, or personas. Such efforts have been motivated by the goals of better understanding the relationships between privacy attitudes, concerns and behaviors, and of helping end users make better privacy decisions.
The focus of the
- The use of segmentations and personas for representing privacy concerns
- Critiques of existing approaches and explorations of the inherent limitations of privacy segmentations or privacy personas
- New paradigms and instruments for understanding, measuring, and modeling privacy concerns, including machine learning based approaches
- Evaluations and critiques of existing instruments for measuring privacy concerns
- The role of context, personality, experiences, and other traits in influencing privacy concerns
- The relationship between privacy concerns, attitudes, and behavior
- Algorithms and tools for providing personalized privacy recommendations
- Other topics related to measuring, modeling, and characterizing privacy concerns
Email inquiries may be sent to: firstname.lastname@example.org or email@example.com
Alessandro Acquisti, Carnegie Mellon University
Bart Knijnenburg, University of California, Irvine
Norman Sadeh, Carnegie Mellon University
Allison Woodruff, Google