Abstract
Data privacy protection is crucial in the era of big data, and although access control mechanisms can effectively prevent privacy leakage, existing access control mechanisms of social networks rarely consider users’ personal privacy preferences in the process of generating access control policies, so they cannot provide personalized services to users. We proposed an intelligent access control mechanism based on users’ privacy preferences by extracting their privacy preference values through a quantifiable analysis mechanism, and then using the values and some key user social resource information as feature vectors. The experiments show that this mechanism can automatically generate appropriate access control policies to meet the potential privacy needs of different users, so as to better protect the privacy of social network data.
Published Version
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