Research And Modeling On Information Dissemination And Trust Mechanism In P2P Social Network

Online Social Network (OSN) provides the primary method for sharing and constructing and searching information to users. It is becoming increasing popular network communication. Online Social Network has been a research hot spot in social network and complicated network and Internet application. In Online Social Network, data privacy caused by data centralized management is a major challenge. In this project, using Social Network Analysis (SNA) in sociology and Data Mining and Graph theory and probability theory, we do more research on the proposed problem in Online Social Network and obtained the innovative research result with theoretical value and practical significance.1. The distributed P2P Social Network based on peer-to-peer computing model is built up. Using Social Network Analysis (SNA), we establish a hierarchical P2P Social Network model according to the social distance showing social similarity of peers and the centrality metric showing the importance of peers, which changes the centralized data management into distributed management, to resolve the inherent disadvantage of centralized data management.2. We propose highly efficient social-aware routing algorithm on resource searching and publishing in P2P Social Network. Information dissemination mechanisms are set up by using social distance and social similarity among peers. The resource and messages are forwarded through the key peers and bridge peers in the network. The routing algorithm deduces searching overhead and improves information transmission efficiency.3. The trust model is constructed in P2P Social Network, and the trust evaluation mechanism on peer is set up. We exploit social relationship among peers to set the reputation and evaluate the trust, and design trust (including social-trust and transaction-trust) updating algorithm after each transaction. According to peer trust we define the access authority in order to achieve authorized access and deduce the malicious behavior, and effectively avoid the leaking of users'data privacy.Through theoretical analysis and simulation evaluation, we will validate the proposed model and schemes. The research will provide a theoretical foundation and method support for the optimization of next-generation social networks, thus with theoretical significance and practical value.