In spite of that the promising features of social networking services can be provided by MSNs, there exist new challenges . Specially, as a typical multimedia service in an M-MSN, the personalized content query may expose a user’s individual information to service providers. For example, a user’s queries could be obtained and recorded by Google to analyze his/her concerns and preferences. Once users browse social networking sites and press the “Facebook Like” button, their individual information and preferences, such as identity and location, are exposed. Obviously, without a careful protection, users’ privacy will be a critical issue in these applications. The privacy issues become more and more important [58, 66-70]. For example, the location privacy has become a serious concern for users when they use the location-based services. Besides, as autonomous mobile social applications have been easy to download nowadays, the user’s personal preferences such as his friends nearby and the interested content, etc., may be revealed when using these autonomous mobile social applications. Therefore, there have been tremendous efforts to protect the privacy of users.
Zhu et al.  study to protect users’ interest information to provide the secure friend discovery process in MSNs. They propose a privacy preserving and fairness- aware friend matching protocol. In the protocol, the blind vector transformation technique is used to protect users’ interest by hiding the relationship of the original interest with the transformed vector. Li et al.  investigate the privacy protection in user profile matching and define two privacy levels. The authors propose two distributed privacy protection schemes for profile matching which are private set- intersection protocol and private cardinality of set-intersection protocol. Lu et al.  study the location privacy for users and propose a link-layer based location privacy protocol. As the protection is deployed at the link-layer, even the attacker gets the user’s location information, the attacker cannot know how long the user has stayed in the current location.
Lu et al.  propose a privacy-preserving method for location privacy in MSNs which let users use pseudo-ID in the network. Because the pseudo-ID is frequently changed at different locations, the user’s past, current and future locations can be protected. Wang et al.  propose a location-aware location privacy protection scheme. It allows users to define the dynamic and diverse privacy requirement according to different locations. Guo et al.  investigate the privacy problems in the content dissemination process by focusing the users’ social information privacy and the dissemination content privacy. The authors propose a privacy-preserving social-assisted mobile content dissemination scheme. By using the verified identical attributes to establish users’ potential social relationships, the proposed scheme can only provide the content to the appropriate users in a cryptographic way to protect the privacy of the user and the content.