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Friend is Calling: Exploiting Mobile Phone Data to Help Users in Setting their Privacy Preferences

Christin, Delphine and Bentolila, A. and Hollick, Matthias (2012):
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), [Conference or Workshop Item]

Abstract

A continuously increasing number of pictures and videos is being shared in online social networks. Currently, users manually confine access to the contents shared. This configuration process can rapidly become cumbersome for users sharing a large amount of content, and, as a result, they may be tempted to rush through the process or leave the default settings unchanged. This can seriously endanger their privacy if inappropriate users are authorized to access sensitive data. In order to reduce the burden on the users as well as enhance their privacy protection, we propose to leverage in- formation already available on their mobile phone as a basis for recommendations on how to set their privacy preferences. To this end, we conducted a user study exploring the differences between users belonging to different social groups, in terms of communication patterns. We have designed clas- sifiers based on mobile phone data to distinguish members of different social groups, and we have evaluated these clas- sifiers using a real-world dataset. The results show that friends can be easily identified using call and short messages logs, while identifying colleagues requires additional information.

Item Type: Conference or Workshop Item
Erschienen: 2012
Creators: Christin, Delphine and Bentolila, A. and Hollick, Matthias
Title: Friend is Calling: Exploiting Mobile Phone Data to Help Users in Setting their Privacy Preferences
Language: German
Abstract:

A continuously increasing number of pictures and videos is being shared in online social networks. Currently, users manually confine access to the contents shared. This configuration process can rapidly become cumbersome for users sharing a large amount of content, and, as a result, they may be tempted to rush through the process or leave the default settings unchanged. This can seriously endanger their privacy if inappropriate users are authorized to access sensitive data. In order to reduce the burden on the users as well as enhance their privacy protection, we propose to leverage in- formation already available on their mobile phone as a basis for recommendations on how to set their privacy preferences. To this end, we conducted a user study exploring the differences between users belonging to different social groups, in terms of communication patterns. We have designed clas- sifiers based on mobile phone data to distinguish members of different social groups, and we have evaluated these clas- sifiers using a real-world dataset. The results show that friends can be easily identified using call and short messages logs, while identifying colleagues requires additional information.

Title of Book: Proceedings of the 4th International Workshop on Security and Privacy in Spontaneous Interaction and Mobile Phone Use (IWSSI/SPMU)
Uncontrolled Keywords: Secure Things
Divisions: LOEWE > LOEWE-Zentren > CASED – Center for Advanced Security Research Darmstadt
LOEWE > LOEWE-Zentren
LOEWE
Date Deposited: 31 Dec 2016 11:08
Identification Number: TUD-CS-2012-0120
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