Biblio

Searchable Encryption (SE) schemes provide security and privacy to the cloud data. The existing SE approaches enable multiple users to perform search operation by using various schemes like Broadcast Encryption (BE), Attribute-Based Encryption (ABE), etc. However, these schemes do not allow multiple users to perform the search operation over the encrypted data of multiple owners. Some SE schemes involve a Proxy Server (PS) that allow multiple users to perform the search operation. However, these approaches incur huge computational burden on PS due to the repeated encryption of the user queries for transformation purpose so as to ensure that users' query is searchable over the encrypted data of multiple owners. Hence, to eliminate this computational burden on PS, this paper proposes a secure proxy server approach that performs the search operation without transforming the user queries. This approach also returns the top-k relevant documents to the user queries by using Euclidean distance similarity approach. Based on the experimental study, this approach is efficient with respect to search time and accuracy.

The hyperlink structure of World Wide Web is modeled as a directed, dynamic, and huge web graph. Web graphs are analyzed for determining page rank, fighting web spam, detecting communities, and so on, by performing tasks such as clustering, classification, and reachability. These tasks involve operations such as graph navigation, checking link existence, and identifying active links, which demand scanning of entire graphs. Frequent scanning of very large graphs involves more I/O operations and memory overheads. To rectify these issues, several data structures have been proposed to represent graphs in a compact manner. Even though the problem of representing graphs has been actively studied in the literature, there has been much less focus on representation of dynamic graphs. In this paper, we propose Tree-Dictionary-Representation (TDR), a compressed graph representation that supports dynamic nature of graphs as well as the various graph operations. Our experimental study shows that this representation works efficiently with limited main memory use and provides fast traversal of edges.