Database outsourcing is an emerging paradigm in cloud computing. The increase in spatial data has led organizations to upload their data onto third-party service providers. Outsourcing entails low cost, dynamic storage and high computational power, as it enables convenient, on-demand network access to a shared pool of computing resources (e.g., networks, servers, storage, applications). Giving control to untrusted third-party servers has security concerns such as confidentiality and privacy. Privacy concerns can be resolved by hiding database from server and attackers, hiding the distribution of spatial points in the space and protecting user query and its result. Therefore, we propose an approach based on cryptographic transformation to perform efficient and accurate query processing at the cloud server in order overcome the security concerns associated with cloud computing.
Nowadays, social network sites; such as Facebook and Twitter, have tremendous number of users in their repositories. Having this huge amount of data requires analyzing them to get statistics about the users and their interests. The information gained from mining social networks can be used in various applications such as recommendations, influence analysis and customer segmentation. The goal of the research group is to devise new techniques for extracting meaningful information inside today's social networks.