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Article Dans Une Revue Pervasive and Mobile Computing Année : 2016

A Machine-Learning Based Approach to Privacy-Aware Information-Sharing in Mobile Social Networks

Résumé

Contextual information about users is increasingly shared on mobile social networks. Examples of such information include users' locations, events, activities, and the co-presence of others in proximity. When disclosing personal information, users take into account several factors to balance privacy, utility and convenience -- they want to share the ``right'' amount and type of information at each time, thus revealing a selective sharing behavior depending on the context, with a minimum amount of user interaction. In this article, we present SPISM, a novel information-sharing system that decides (semi-)automatically, based on personal and contextual features, whether to share information with others and at what granularity, whenever it is requested. SPISM makes use of (active) machine-learning techniques, including cost-sensitive multi-class classifiers based on support vector machines. SPISM provides both ease of use and privacy features: It adapts to each user's behavior and predicts the level of detail for each sharing decision. Based on a personalized survey about information sharing, which involves 70 participants, our results provide insight into the most influential features behind a sharing decision, the reasons users share different types of information and their confidence in such decisions. We show that SPISM outperforms other kinds of policies; it achieves a median proportion of correct sharing decisions of 72\% (after only 40 manual decisions). We also show that SPISM can be optimized to gracefully balance utility and privacy, but at the cost of a slight decrease in accuracy. Finally, we assess the potential of a one-size-fits-all version of SPISM.
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Dates et versions

hal-01108962 , version 1 (24-02-2015)

Identifiants

Citer

Igor Bilogrevic, Kévin Huguenin, Berker Ağir, Murtuza Jadliwala, Maria Gazaki, et al.. A Machine-Learning Based Approach to Privacy-Aware Information-Sharing in Mobile Social Networks. Pervasive and Mobile Computing, 2016, 25, pp.125-142. ⟨10.1016/j.pmcj.2015.01.006⟩. ⟨hal-01108962⟩
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