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Authenticated Query Processing
PhD Thesis Proposal Defence Title: "Authenticated Query Processing" by Mr. Stavros Papadopoulos Abstract: Under the database outsourcing paradigm, a data owner (e.g., a company or corporate organization) delegates the administration of its database to a third-party service provider. Clients direct their queries to the provider, without contacting the owner. The provider is considered untrustworthy and may tamper with the results. Authenticated query processing allows the owner to cryptographically ??mark?? its dataset through a public-key cryptosystem, and the provider to associate a proof of correctness with the returned results. This proof is usually generated by authenticated data structures (ADSs), which are similar to traditional indices, but they are augmented with cryptographic information. The clients can efficiently verify the proof using the public key of the owner. In this proposal we study two important problems in database outsourcing: (i) spatial authentication, and (ii) continuous authentication on relational streams. Regarding the first topic, we introduce the MR-tree, a space-efficient ADS that supports fast processing and verification of spatial queries (e.g., ranges, nearest neighbor queries, etc.). The MR-Tree outperforms the existing solutions on all performance metrics. We then design the MR*-tree, a modified version of the MR-tree, which significantly reduces the proof size through a novel embedding technique. Finally, whereas most ADSs must be constructed and maintained also by the owner, we outsource the MR- and MR*-tree construction and maintenance to the server, thus relieving the owner from this computationally intensive task. Concerning the second problem, we first address the challenges posed by stream environments, such as the need for fast structure updating, support for continuous query processing and authentication, and provision for temporal completeness. Specifically, in addition to the correctness of individual results, the client must be able to verify that there are no missing results in between data updates. Then we present a comprehensive set of methods covering relational streams, including the following: (i) We describe REF, a technique that provides result correctness and temporal completeness but incurs false transmissions, i.e., the server has to inform the clients whenever there is a data update, even if their results are not affected. (ii) We propose CADS, which minimizes the processing and transmission overhead through an elaborate indexing scheme and a virtual caching mechanism. (iii) We include an analytical study to determine the optimal indexing granularity. (iv) We extend CADS for the case that the data distribution changes over time. Finally, we evaluate the effectiveness of our techniques through extensive experiments. Date: Monday, 22 June 2009 Time: 3:00pm-5:00pm Venue: Room 3501 lifts 25-26 Committee Members: Prof. Dimitris Papadias (Supervisor) Prof. Mounir Hamdi (Chairperson) Dr. Lei Chen Prof. Dik-Lun Lee **** ALL are Welcome ****