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k-subscription: Privacy-Preserving Microblogging Browsing Through Obfuscation
To address these privacy concerns, we propose k-subscription: an obfuscation-based approach that enables users to follow privacy-sensitive channels, while, at the same time, making it difficult for the microblogging service to find out their actual interests. Our method relies on obfuscation: in addition to each privacy-sensitive channel, users are encouraged to randomly follow k −1 other channels they are not interested in. In this way (i) their actual interests are hidden in random selections, and (ii) each user contributes in hiding the real interests of other users. Our analysis indicates that k-subscription makes it difficult for attackers to pinpoint a user’s interests with significant confidence. We show that this confidence can be made predictably small by slightly adjusting k while adding a reasonably low overhead on the user’s system.
Author(s):
Panagiotis Papadopoulos
Institute of Computer Science, Foundation for Research and Technology - Hellas
Greece
Antonis Papadogiannakis
Institute of Computer Science, Foundation for Research and Technology - Hellas
Greece
Michalis Polychronakis
Computer Science Department, Columbia University
United States
Apostolis Zarras
Ruhr - University Bochum
Germany
Thorsten Holz
Ruhr - University Bochum
Germany
Evangelos P. Markatos
Institute of Computer Science, Foundation for Research and Technology - Hellas
Greece