Behavioral Tendency Obfuscation Framework for Personalization Services
Web service providers collect user behaviors, such as purchases or locations, and use this information to provide personalized content. While no provider can collect behavioral information across different service providers, the behaviors for all service providers are accumulated in a user’s terminal. If a provider could analyze these behaviors stored in the terminal, it could provide more valuable services to the user. There is a problem, however, in that sensitive user information would be revealed when the provider obtained behaviors related to other services. This sensitive information consists of the user’s behaviors and characteristic tendencies analyzed from the collected information. In this paper, we propose a model for preserving privacy, called ρ-tendency certainty, which considers breaches of privacy from collected information. We also propose a behavioral tendency obfuscation framework, which sends dummy queries to service providers in order to satisfy ρ-tendency certainty. Experimental results show that the proposed framework can satisfy ρ-tendency certainty with a few number of dummy queries and create dummies within 1 msec, thus the proposed framework is applicable to real services.
Keywordsprivacy personalization services behavioral tendency obfuscation framework
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