Mobile social applications have been widely used by Internet users. Users can efficiently acquire many kinds of information and share their statuses by various social platforms. However, when a user intends to share information through the user's social applications, the user can set the access permission only before the information is posted. Once the information is posted, it is completely beyond the user's control. Specifically, during the recommendation process (for friend or information) in social applications, a user cannot control who can get the recommendation and access his/her information. If one user is accessed by another malicious user, his/her privacy information can be disclosed, and even be further misused for malicious attacks. In this article, we propose Trust2Privacy, a trust-based access control mechanism to protect the personalized privacy of users after posting their information, which can effectively realize the transformation from trust to privacy. First, to represent the relations accurately among users, we define the direction of trust among users according to the user-follow status. Then we combine the similarity, correlation, and interaction among users to calculate the trust values. Considering the fuzzy relationship between the multi-dimensional features and trust levels, we propose a fuzzy comprehensive evaluation algorithm to compute the fuzzy trust. Moreover, for the sake of the high mobility of mobile social networks, we exploit so-called online-to-offline trust evidence to derive the trust value, including taking the location information (e.g., distance, semantics) into consideration. To meet the personalized privacy requirement, we design a filtering algorithm based on the trust relationships and the privacy policy of the target users or posted information, according to which the access requesters can get the list of accessible users or information. This enables achieving the goal of personalized privacy protection. The theoretical analysis and simulation experiment demonstrate that Trust2Privacy is able to achieve personalized privacy protection without bringing negative impact on the availability and usability of mobile social applications.

中文翻译：

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Trust2Privacy：移动社交网络的新型模糊信任至隐私机制

移动社交应用程序已被Internet用户广泛使用。用户可以通过各种社交平台有效地获取多种信息并共享其状态。但是，当用户打算通过用户的社交应用程序共享信息时，用户只能在发布信息之前设置访问权限。信息发布后，将完全超出用户的控制范围。具体地，在社交应用的推荐过程中（针对朋友或信息），用户无法控制谁可以获取推荐并访问他/她的信息。如果一个用户被另一个恶意用户访问，则他/她的隐私信息可以被泄露，甚至被进一步滥用以进行恶意攻击。在本文中，我们提出了Trust2Privacy，一种基于信任的访问控制机制，用于保护用户发布信息后的个性化隐私，可以有效地实现从信任到隐私的转变。首先，为了准确表示用户之间的关系，我们根据用户关注状态定义了用户之间的信任方向。然后，我们结合用户之间的相似性，相关性和交互性来计算信任值。考虑到多维特征与信任度之间的模糊关系，提出了一种模糊综合评价算法来计算模糊信任度。此外，出于移动社交网络的高度移动性，我们利用所谓的在线到离线信任证据来得出信任值，包括考虑位置信息（例如，距离，语义）。为了满足个性化隐私需求，我们设计了基于目标用户或发布信息的信任关系和隐私策略的过滤算法，访问请求者可以根据该过滤算法获得可访问用户或信息的列表。这样可以实现个性化隐私保护的目标。理论分析和仿真实验表明，Trust2Privacy能够实现个性化的隐私保护，而不会给移动社交应用程序的可用性和可用性带来负面影响。这样可以实现个性化隐私保护的目标。理论分析和仿真实验表明，Trust2Privacy能够实现个性化的隐私保护，而不会给移动社交应用程序的可用性和可用性带来负面影响。这样可以实现个性化隐私保护的目标。理论分析和仿真实验表明，Trust2Privacy能够实现个性化的隐私保护，而不会给移动社交应用程序的可用性和可用性带来负面影响。