More Web Proxy on the site http://driver.im/

research-article

Can I Help You Setting Your Privacy? A Survey-based Exploration of Users' Attitudes towards Privacy Suggestions

Authors:

Delphine Reinhardt,

Franziska Engelmann,

Matthias HollickAuthors Info & Claims

MoMM 2015: Proceedings of the 13th International Conference on Advances in Mobile Computing and Multimedia

Pages 347 - 356

https://doi.org/10.1145/2837126.2837130

Published: 11 December 2015 Publication History

Abstract

Even avid users of mobile applications turn a blind eye to privacy settings. Still mobile applications remain the key means by which users share sensitive personal information. It is unclear if users just do not care, if they are missing the appropriate tools or user interfaces, or if they live in the delusion of being in control of their data. We argue that non-user-friendly design presents a key obstacle in making privacy controls work: it hinders users to effectively set up and maintain privacy settings. Our ultimate goal is to support the user by automatically suggesting access control lists based on an analysis of her communication metadata. To guide us in the design of such privacy suggestions, we perform an explorative questionnaire-based study with 42 participants. Our results confirm that users are overtaxed with existing schemes. We identify the expectations and preferences of users, thus facilitating the design of improved solutions.

References

[1]

Facebook Statistics. Online: http://newsroom.fb.com/company-info/ (accessed 04.15), 2015.

[2]

S. Amershi, J. Fogarty, and D. Weld. Regroup: Interactive Machine Learning for On-demand Group Creation in Social Networks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), 2012.

Digital Library

[3]

D. Christin, A. Bentolila, and M. Hollick. Friend is Calling: Exploiting Mobile Phone Data to Help Users in Setting their Privacy Preferences. In Proceedings of the 4th International Workshop on Security and Privacy in Spontaneous Interaction and Mobile Phone Use (IWSSI/SPMU), 2012.

[4]

N. Eagle and A. S. Pentland. Reality Mining: Sensing Complex Social Systems. Personal Ubiquitous Computing, 2006.

Digital Library

[5]

N. Eagle, A. S. Pentland, and D. Lazer. Inferring Friendship Network Structure by Using Mobile Phone Data. Proceedings of the National Academy of Sciences, 2009.

[6]

H. Ebel, L.-I. Mielsch, and S. Bornholdt. Scale-free Topology of E-mail Networks. Physical review E, 66(3), 2002.

[7]

L. Fang and K. LeFevre. Privacy Wizards for Social Networking Sites. In Proceedings of the 19th ACM International Conference on World Wide Web (WWW), 2010.

Digital Library

[8]

J. L. Herlocker, J. A. Konstan, and J. Riedl. Explaining Collaborative Filtering Recommendations. In Proceedings of the 3rd ACM Conference on Computer Supported Cooperative Work (CSCW), 2000.

Digital Library

[9]

M. Johnson, S. Egelman, and S. M. Bellovin. Facebook and Privacy: It's Complicated. In Proceedings of the 8th ACM Symposium on Usable Privacy and Security (SOUPS), 2012.

Digital Library

[10]

P. G. Kelley, R. Brewer, Y. Mayer, L. F. Cranor, and N. Sadeh. An Investigation into Facebook Friend Grouping. In Proceedings of the 13th IFIP TC 13 International Conference on Human-computer Interaction (INTERACT), 2011.

Digital Library

[11]

P. G. Kelley, P. Hankes Drielsma, N. Sadeh, and L. F. Cranor. User-controllable Learning of Security and Privacy Policies. In Proceedings of the 1st ACM Workshop on AISec, 2008.

Digital Library

[12]

G. Kossinets and D. J. Watts. Empirical Analysis of an Evolving Social Network. Science, 2006.

[13]

M. Madejski, M. Johnson, and S. M. Bellovin. A Study of Privacy Settings Errors in an Online Social Network. In Proceedings of the 10th IEEE International Conference on Pervasive Computing and Communications (PERCOM Workshops), 2012.

[14]

J.-K. Min, J. Wiese, J. I. Hong, and J. Zimmerman. Mining Smartphone Data to Classify Life-facets of Social Relationships. In Proceedings of the 16th ACM Conference on Computer Supported Cooperative Work (CSCW), 2013.

Digital Library

[15]

S. H. Mirisaee, S. Noorzadeh, A. Sami, and R. Sameni. Mining Friendship from Cell-Phone Switch Data. In Proceedings of the IEEE 3rd International Conference on Human-Centric Computing (HumanCom), 2010.

[16]

J. Mugan, T. Sharma, and N. Sadeh. Understandable Learning of Privacy Preferences Through Default Personas and Suggestions. Technical Report CMU-ISR-11-112, Carnegie Mellon University, http://ra.adm.cs.cmu.edu/anon/anon/isr2011/CMU-ISR-11-112.pdf (accessed 04.15), 2011.

[17]

J.-P. Onnela, J. Saramäki, J. Hyvönen, G. Szabó, D. Lazer, K. Kaski, J. Kertész, and A.-L. Barabási. Structure and Tie Strengths in Mobile Communication Networks. Proceedings of the National Academy of Sciences, 2007.

[18]

C. Pring. 100 Social Media Statistics for 2012. Online: http://thesocialskinny.com/100-social-media-statistics-for-2012/ (accessed 04.15), 2012.

[19]

E. Protalinski. Facebook has over 425 Million Mobile Users. Online: http://www.zdnet.com/article/facebook-has-over-425-million-mobile-users/ (accessed 04.15), 2012.

[20]

D. Quercia and L. Capra. FriendSensing: Recommending Friends Using Mobile Phones. In Proceedings of the 3rd ACM Conference on Recommender Systems (RecSys), 2009.

Digital Library

[21]

R. Ravichandran, M. Benisch, P. G. Kelley, and N. Sadeh. Capturing Social Networking Privacy Preferences: Can Default Policies Help Alleviate Tradeoffs Between Expressiveness and User Burden? In Proceedings of the 5th ACM Symposium on Usable Privacy and Security (SOUPS), 2009.

Digital Library

[22]

D. Reinhardt, F. Engelmann, A. Moerov, and M. Hollick. Show Me Your Phone, I Will Tell You Who Your Friends Are: Analyzing Smartphone Data To Identify Social Relationships. In Proceedings of the 14th ACM International Conference on Mobile and Ubiquitous Multimedia (MUM), 2015.

Digital Library

[23]

Y. Shen and R. Jin. Learning Personal + Social Latent Factor Model for Social Recommendation. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012.

Digital Library

[24]

Y. Song, L. Zhang, and C. L. Giles. Automatic Tag Recommendation Algorithms for Social Recommender Systems. ACM Transactions on the Web (TWEB), 5(1), 2011.

Digital Library

[25]

A. Squicciarini, F. Paci, and S. Sundareswaran. PriMa: An Effective Privacy Protection Mechanism for Social Networks. In Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security (ASIACCS), 2010.

Digital Library

[26]

Y. Wang, P. G. Leon, K. Scott, X. Chen, A. Acquisti, and L. F. Cranor. Privacy Nudges for Social Media: An Exploratory Facebook Study. In Proceedings of the 22nd International Conference on World Wide Web (WWW), 2013.

Digital Library

[27]

Y. Wang, G. Norcie, S. Komanduri, A. Acquisti, P. G. Leon, and L. F. Cranor. "I Regretted the Minute I Pressed Share": A Qualitative Study of Regrets on Facebook. In Proceedings of the Seventh Symposium on Usable Privacy and Security (SOUPS), 2011.

Digital Library

[28]

J. Watson, A. Besmer, and H. R. Lipford. +Your Circles: Sharing Behavior on Google+. In Proceedings of the 8th ACM Symposium on Usable Privacy and Security (SOUPS), 2012.

Digital Library

[29]

J. Wiese, P. G. Kelley, L. F. Cranor, L. Dabbish, J. I. Hong, and J. Zimmerman. Are You Close with Me? Are You Nearby?: Investigating Social Groups, Closeness, and Willingness to Share. In Proceedings of the 13th ACM International Conference on Ubiquitous Computing (UbiComp), 2011.

Digital Library

[30]

X. Yang, Y. Guo, and Y. Liu. Bayesian-Inference based Recommendation in Online Social Networks. In Proceedings of the 30th IEEE Conference on Computer Communications (INFOCOM), 2011.

Cited By

Alamari JAlshehri A(2024)Adaptive privacy permissions for social media webMultimedia Tools and Applications10.1007/s11042-024-20423-4Online publication date: 4-Nov-2024
https://doi.org/10.1007/s11042-024-20423-4
Shams SReinhardt D(2023)Vision: Supporting Citizens in Adopting Privacy Enhancing TechnologiesProceedings of the 2023 European Symposium on Usable Security10.1145/3617072.3617105(253-259)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3617072.3617105
Cofone I(2023)NotesThe Privacy Fallacy10.1017/9781108995825.010(173-242)Online publication date: 16-Nov-2023
https://doi.org/10.1017/9781108995825.010
Show More Cited By

Index Terms

Can I Help You Setting Your Privacy? A Survey-based Exploration of Users' Attitudes towards Privacy Suggestions

Recommendations

Privacy attitudes and privacy behaviour

Do people really care about their privacy? Surveys show that privacy is a primary concern for citizens in the digital age. On the other hand, individuals reveal personal information for relatively small rewards, often just for drawing the attention of ...
Is pay-or-consent for privacy justifiable? Evidence from different users' privacy attitudes toward behavioral data collection in South Korea
Abstract
As regulators began prohibiting online platforms from collecting personal data based on the “take-it-or-leave-it” basis, platform firms must adopt more refined user consent rules such as the pay-or-consent approach. Ensuring sufficient user ...
Highlights
- Ensuring sufficient user options can increase or decrease user welfare.
- Enforcing identical user consent conditions for all users is inappropriate.
- Three user segments in terms of privacy attitudes in free online platforms are ...
Users' Privacy Issues with E-learning in Library2.0
MINES '09: Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 01

This article discusses the users' privacy issues when they learn in Libray2.0. The authors classify learners' privacy issues in Library2.0 into four categories: users' personal information, users' seeking behavior privacy, threat from the third party ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

MoMM 2015: Proceedings of the 13th International Conference on Advances in Mobile Computing and Multimedia

December 2015

422 pages

ISBN:9781450334938

DOI:10.1145/2837126

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Johannes Kepler University, Linz, Austria
@WAS: International Organization of Information Integration and Web-based Applications and Services

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 December 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article
Research
Refereed limited

Conference

MoMM 2015

MoMM 2015: The 13th International Conference on Advances in Mobile Computing and Multimedia

December 11 - 13, 2015

Brussels, Belgium

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
167
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)1

Reflects downloads up to 14 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Alamari JAlshehri A(2024)Adaptive privacy permissions for social media webMultimedia Tools and Applications10.1007/s11042-024-20423-4Online publication date: 4-Nov-2024
https://doi.org/10.1007/s11042-024-20423-4
Shams SReinhardt D(2023)Vision: Supporting Citizens in Adopting Privacy Enhancing TechnologiesProceedings of the 2023 European Symposium on Usable Security10.1145/3617072.3617105(253-259)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3617072.3617105
Cofone I(2023)NotesThe Privacy Fallacy10.1017/9781108995825.010(173-242)Online publication date: 16-Nov-2023
https://doi.org/10.1017/9781108995825.010
Kqiku LReinhardt D(2023)Lengthy early morning instant messages reveal more than you think: Analysing interpersonal relationships using mobile communication metadataPervasive and Mobile Computing10.1016/j.pmcj.2023.10178191(101781)Online publication date: Apr-2023
https://doi.org/10.1016/j.pmcj.2023.101781
Tillmann AKqiku LReinhardt DWeisser CSäfken BKneib T(2022)Privacy Estimation on Twitter: Modelling the Effect of Latent Topics on Privacy by Integrating XGBoost, Topic and Generalized Additive Models2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00365(2325-2332)Online publication date: Dec-2022
https://doi.org/10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00365
Mosca FSuch J(2022)An explainable assistant for multiuser privacyAutonomous Agents and Multi-Agent Systems10.1007/s10458-021-09543-536:1Online publication date: 15-Jan-2022
https://doi.org/10.1007/s10458-021-09543-5
Kaskina AKaskina A(2022)Citizen Privacy Profile FrameworkCitizen Privacy Framework10.1007/978-3-031-06021-2_3(21-69)Online publication date: 16-May-2022
https://doi.org/10.1007/978-3-031-06021-2_3
Kaskina AKaskina A(2022)Insights into Privacy ResearchCitizen Privacy Framework10.1007/978-3-031-06021-2_2(9-19)Online publication date: 16-May-2022
https://doi.org/10.1007/978-3-031-06021-2_2
Elahi HWang G(2019)A Participatory Privacy Protection Framework for Smart-Phone Application Default SettingsSecurity in Computing and Communications10.1007/978-981-13-5826-5_13(168-182)Online publication date: 24-Jan-2019
https://doi.org/10.1007/978-981-13-5826-5_13
Kaskina A(2017)Differentiated User Privacy Support in the Digital SocietyWirtschaftsinformatik in Theorie und Praxis10.1007/978-3-658-17613-6_11(141-152)Online publication date: 8-Jun-2017
https://doi.org/10.1007/978-3-658-17613-6_11
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents