demonstration

A privacy recommendation wizard for users of social networking sites

Authors:

Lujun Fang,

Heedo Kim,

Kristen LeFevre,

Aaron TamiAuthors Info & Claims

CCS '10: Proceedings of the 17th ACM conference on Computer and communications security

Pages 630 - 632

https://doi.org/10.1145/1866307.1866378

Published: 04 October 2010 Publication History

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Abstract

Privacy is a huge problem for users of social networking sites. While sites like Facebook allow individual users to personalize fine-grained privacy settings, this has proven quite difficult for average users. This demonstration illustrates a machine learning privacy wizard, or recommendation tool, that we have built at the University of Michigan. The wizard is based on the underlying observation that real users conceive their privacy preferences (which friends should see which data items) based on an implicit structure. Thus, after asking the user a limited number of carefully-chosen questions, it is usually possible to build a machine learning model that accurately predicts the user's privacy preferences. This model, in turn, can be used to recommend detailed privacy settings for the user. Our demonstration wizard runs as a third-party Facebook application. Conference attendees will be able to "test-drive" the wizard by installing it on their own Facebook accounts.

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Cited By

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Nakamura TTesfay WKiyomoto SSerna J(2017)Default Privacy Setting Prediction by Grouping User’s Attributes and Settings PreferencesData Privacy Management, Cryptocurrencies and Blockchain Technology10.1007/978-3-319-67816-0_7(107-123)Online publication date: 13-Sep-2017
https://doi.org/10.1007/978-3-319-67816-0_7
Nakamura TKiyomoto STesfay WSerna J(2017)Easing the Burden of Setting Privacy Preferences: A Machine Learning ApproachInformation Systems Security and Privacy10.1007/978-3-319-54433-5_4(44-63)Online publication date: 18-Feb-2017
https://doi.org/10.1007/978-3-319-54433-5_4
Golbeck JMauriello M(2016)User Perception of Facebook App Data Access: A Comparison of Methods and Privacy ConcernsFuture Internet10.3390/fi80200098:4(9)Online publication date: 25-Mar-2016
https://doi.org/10.3390/fi8020009
Show More Cited By

Index Terms

A privacy recommendation wizard for users of social networking sites
1. Security and privacy
  1. Database and storage security
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Theory of database privacy and security

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Information & Contributors

Information

Published In

CCS '10: Proceedings of the 17th ACM conference on Computer and communications security

October 2010

782 pages

ISBN:9781450302456

DOI:10.1145/1866307

General Chair:
Ehab Al-Shaer
University of North Carolina, Charlotte, USA
,
Program Chairs:
Angelos D. Keromytis
Columbia University, USA
,
Vitaly Shmatikov
University of Texas at Austin, USA

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 October 2010

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CCS '10

Sponsor:

SIGSAC

CCS '10: 17th ACM Conference on Computer and Communications Security 2010

October 4 - 8, 2010

Illinois, Chicago, USA

Acceptance Rates

CCS '10 Paper Acceptance Rate 55 of 325 submissions, 17%;

Overall Acceptance Rate 1,261 of 6,999 submissions, 18%

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CCS '25

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sigsac

ACM SIGSAC Conference on Computer and Communications Security

October 13 - 17, 2025

Taipei , Taiwan

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Nakamura TTesfay WKiyomoto SSerna J(2017)Default Privacy Setting Prediction by Grouping User’s Attributes and Settings PreferencesData Privacy Management, Cryptocurrencies and Blockchain Technology10.1007/978-3-319-67816-0_7(107-123)Online publication date: 13-Sep-2017
https://doi.org/10.1007/978-3-319-67816-0_7
Nakamura TKiyomoto STesfay WSerna J(2017)Easing the Burden of Setting Privacy Preferences: A Machine Learning ApproachInformation Systems Security and Privacy10.1007/978-3-319-54433-5_4(44-63)Online publication date: 18-Feb-2017
https://doi.org/10.1007/978-3-319-54433-5_4
Golbeck JMauriello M(2016)User Perception of Facebook App Data Access: A Comparison of Methods and Privacy ConcernsFuture Internet10.3390/fi80200098:4(9)Online publication date: 25-Mar-2016
https://doi.org/10.3390/fi8020009
Amor IBenbernou SOuziri MMalik ZMedjahed B(2016)Discovering Best Teams for Data Leak-Aware Crowdsourcing in Social NetworksACM Transactions on the Web10.1145/281457310:1(1-27)Online publication date: 8-Feb-2016
https://dl.acm.org/doi/10.1145/2814573
Emilio Diaz Eerreyra NSchawel JHeisel MMeske C(2016)Addressing self-disclosure in social media: An instructional awareness approach2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)10.1109/AICCSA.2016.7945815(1-6)Online publication date: Nov-2016
https://doi.org/10.1109/AICCSA.2016.7945815
Naini KAltingovde IKawase RHerder ENiederée C(2015)Analyzing and Predicting Privacy Settings in the Social WebUser Modeling, Adaptation and Personalization10.1007/978-3-319-20267-9_9(104-117)Online publication date: 11-Jun-2015
https://doi.org/10.1007/978-3-319-20267-9_9
Gao BBerendt B(2015)Friends and Circles—A Design Study for Contact Management in Egocentric Online Social NetworksOnline Social Media Analysis and Visualization10.1007/978-3-319-13590-8_7(129-161)Online publication date: 15-Jan-2015
https://doi.org/10.1007/978-3-319-13590-8_7
Rasmussen CDara R(2014)Empowering users through privacy management recommender systems2014 IEEE Canada International Humanitarian Technology Conference - (IHTC)10.1109/IHTC.2014.7147532(1-5)Online publication date: Jun-2014
https://doi.org/10.1109/IHTC.2014.7147532
Rasmussen CDara R(2014)Recommender Systems for Privacy ManagementProceedings of the 2014 IEEE 15th International Symposium on High-Assurance Systems Engineering10.1109/HASE.2014.43(243-244)Online publication date: 9-Jan-2014
https://dl.acm.org/doi/10.1109/HASE.2014.43
Heupel MBourimi MKesdoğan D(2013)Trust and Privacy in the di.me UserwareProceedings, Part III, of the 15th International Conference on Human-Computer Interaction. Users and Contexts of Use - Volume 800610.5555/2959924.2959930(39-48)Online publication date: 21-Jul-2013
https://dl.acm.org/doi/10.5555/2959924.2959930
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Privacy wizards for social networking sites

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Privacy wizards for social networking sites

Uses and gratifications of social networking sites for bridging and bonding social capital

Semantics-Enhanced Privacy Recommendation for Social Networking Sites

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