With the emergence of various social networks, the social media network data is analyzed from the perspective of variety by more and more researchers. The data fusion of multiple social networks relies on user identification across social networks. Concerning the low utilization problem of heterogeneous relation between social networks of the traditional Friend Relationship-based User Identification (FRUI) algorithm, a new Weighted Hypergraph based User Identification (WHUI) algorithm across social networks was proposed. Firstly, the weighted hypergraph was accurately constructed on the friend relation networks to describe the friend relation and the heterogeneous relation in the same network, which improved the accuracy of presenting topological environment of nodes. Then, on the basis of the constructed weighted hypergraph, the cross network similarity between nodes was defined according to the consistency of nodes' topological environment in different networks. Finally, the user pair with the highest cross network similarity was chosen to match each time by combining with the iterative matching algorithm, while two-way authentication and result pruning were added to ensure the recognition accuracy. The experiments were carried out in the DBLP cooperation networks and real social networks. The experimental results show that, compared with the existing FRUI algorithm, the average precision, recall, F of the proposed algorithm is respectively improved by 5.5 percentage points, 3.4 percentage points, 4.6 percentage points in the real social networks. The WHUI algorithm can effectively improve the precision and recall of user identification in practical applications by utilizing only network topology information.

In order to solve the confidentiality issues such as key exposure and attribute revocation of data stored in cloud server, an advanced anonymous privacy-preserving scheme based on Ciphertext-Policy Attributed-Based Encryption (CP_ABE) was proposed by considering confidentiality of data storage and indistinguishability of access. First, the scheme constructed a forward-secure irreversible key-update algorithm to solve key exposure. On the basis of the classified user-group and the advanced Subset-Difference algorithm, fine-grained attribute revocation was implemented with the help of cloud data re-encryption algorithm. The potential interests of user would be concealed when k-anonymity l-diversity data request was introduced based on the homomorphic encryption algorithm. The backward-security of key exposure was realized on the basis of secondary encryption inserted in data response. Under the l-Bilinear Diffie-Hellman Exponent Problem (l-BDHE) assumption, selective security of the proposed scheme was proved in the standard model. The performance advantage of the proposed scheme was demonstrated respectively in terms of efficiency, key length and security.

A distributed application layer multicast model based on Central Ring Carousel algorithm was proposed. The model employed ring as the basic topology unit, constructed carousel on each central node, and built its upper rings topology according to each node's priority. The simulation results indicate that CRCL can improve the performance of streaming media application efficiently, especially in data transmission, convergence time and average path length.