Biblio

In recent years, mobile social networks (MSNs) have developed rapidly and their application fields are becoming more and more widespread. Due to the continuous movement of nodes in mobile social networks, the network topology is very unstable. How to ensure the credibility of network communication is a subject worth studying. In this paper, based on the characteristics of mobile social networks, the definition of trust level is introduced into the DSR routing protocol, and a trusted DSR routing mechanism (TDR) is proposed. The scheme combines the sliding window model to design the calculation method of trust level between nodes and path trust level. The nodes in the network participate in the routing process according to their trust level. When the source node receives multiple routes carried by the response, the appropriate trusted path is selected according to the path trust level. Through simulation analysis, compared with the original DSR protocol, the TDR protocol improves the performance of average delay, route cost and packet delivery fraction, and verifies the reliability and credibility of the TDR protocol.

Mobile social networks (MSNs) facilitate connections between mobile users and allow them to find other potential users who have similar interests through mobile devices, communicate with them, and benefit from their information. As MSNs are distributed public virtual social spaces, the available information may not be trustworthy to all. Therefore, mobile users are often at risk since they may not have any prior knowledge about others who are socially connected. To address this problem, trust inference plays a critical role for establishing social links between mobile users in MSNs. Taking into account the nonsemantical representation of trust between users of the existing trust models in social networks, this paper proposes a new fuzzy inference mechanism, namely MobiFuzzyTrust, for inferring trust semantically from one mobile user to another that may not be directly connected in the trust graph of MSNs. First, a mobile context including an intersection of prestige of users, location, time, and social context is constructed. Second, a mobile context aware trust model is devised to evaluate the trust value between two mobile users efficiently. Finally, the fuzzy linguistic technique is used to express the trust between two mobile users and enhance the human's understanding of trust. Real-world mobile dataset is adopted to evaluate the performance of the MobiFuzzyTrust inference mechanism. The experimental results demonstrate that MobiFuzzyTrust can efficiently infer trust with a high precision.