Biblio

The rapid development of the Internet and ecommerce has brought a lot of convenience to people's life. Personalized recommendation technology provides users with services that they may be interested according to users' information such as personal characteristics and historical behaviors. The research of personalized recommendation has been a hot point of data mining and social networks. In this paper, we focus on resolving the problem of data sparsity based on users' rating data and social network information, introduce a set of new measures for social trust and propose a novel personalized recommendation algorithm based on matrix factorization combining trust relevancy. Our experiments were performed on the Dianping datasets. The results show that our algorithm outperforms traditional approaches in terms of accuracy and stability.

Matrix factorization (MF) has been proved to be an effective approach to build a successful recommender system. However, most current MF-based recommenders cannot obtain high prediction accuracy due to the sparseness of user-item matrix. Moreover, these methods suffer from the scalability issues when applying on large-scale real-world tasks. To tackle these issues, in this paper a social regularization method called TrustRSNMF is proposed that incorporates the social trust information of users in nonnegative matrix factorization framework. The proposed method integrates trust statements along with user-item ratings as an additional information source into the recommendation model to deal with the data sparsity and cold-start issues. In order to evaluate the effectiveness of the proposed method, a number of experiments are performed on two real-world datasets. The obtained results demonstrate significant improvements of the proposed method compared to state-of-the-art recommendation methods.

Due to openness of the deployed environment and transmission medium, Wireless Sensor Networks (WSNs) suffers from various types of security attacks including Denial of service, Sinkhole, Tampering etc. Securing WSN is achieved a greater research interest and this paper proposes a new secure routing strategy for WSNs based on trust model. In this model, initially the sensor nodes of the network are formulated as clusters. Further a trust evaluation mechanism was accomplished for every sensor node at Cluster Head level to build a secure route for data transmission from sensor node to base station. Here the trust evaluation is carried out only at cluster head and also the cluster head is chosen in such a way the node having rich resources availability. The trust evaluation is a composition of the social trust and data trust. Simulation experiments are conducted over the proposed approach and the performance is measured through the performance metrics such as network lifetime, and Malicious Detection Rate. The obtained performance metrics shows the outstanding performance of proposed approach even in the increased malicious behavior of network.

In recent years, with growing demands towards big data application, various research on context-awareness has once again become active. This paper proposes a new type of context-aware user authentication that controls the authentication level of users, using the context of “physical trust relationship” that is built between users by visual contact. In our proposal, the authentication control is carried out by two mechanisms; “i-Contact” and “k-Contact”. i-Contact is the mechanism that visually confirms the user (owner of a mobile device) using the surrounding users' eyes. The authenticity of users can be reliably assessed by the people (witnesses), even when the user exhibits ambiguous behavior. k-Contact is the mechanism that dynamically changes the authentication level of each user using the context information collected through i-Contact. Once a user is authenticated by eyewitness reports, the user is no longer prompted for a password to unlock his/her mobile device and/or to access confidential resources. Thus, by leveraging the proposed authentication system, the usability for only trusted users can be securely enhanced. At the same time, our proposal anticipates the promotion of physical social communication as face-to-face communication between users is triggered by the proposed authentication system.