Abstract
Social networking sites (SNSs) are increasingly becoming a major type of online applications that facilitate online social interactions and information sharing among a large amount of users. Furthermore, privacy protection is an important issue in social networking. Users are not able to easily specify their access control requirements through the available privacy configuration interface s. An approach assisting online users in composing and managing their access control policies to configure their privacy setting is proposed based on Decision Tree Learning . Moreover, Ontology APIs include social network ontology (SNO) to capture the information semantics in an SNS and an access control ontology (ACO) that is used to store rules from the classifier combining with ex isting access control rules. Therefore, a fine -gained OSN access control model based on semantic web technologies is proposed in order to automatically construct access control rules for the users' privacy settings with the minimal effort from the user.
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