Sensitive-resisting Relation Social Network Privacy Protection Model
نویسنده
چکیده
The existing social network privacy protection method mostly aims at the individuals of the social network, which cannot protect effectively the sensitive relations in the social network. Therefore, this paper proposes a new personalized K_L model. This model requires each sensitive relation with the sensitive relational point have l at least, and also the point with the same requirement has k at least. Thus, the attack has been resisted during the protection of the sensitive relations. Through seeking the most figure of merit sequence and considering individual sensitive attribute, the L-diversity method is applied so as to guarantee the least side and reduce the anonymous cost. Through the data set experiment, this paper proposes new personalized model K_L, which has the high anonymous quality and can effectively protect user's privacy in the social network.
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