Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/3245

CADS: Continuous Authentication on Data Streams

Authors Papadopoulos, Stavros
Yang, Yin
Papadias, Dimitris
Issue Date 2007
Source Proceedings of the Very Large Data Bases Conference (VLDB), Vienna, Austria , pp. 135-146, September 23-28
Summary We study processing and authentication of long-running queries on outsourced data streams. In this scenario, a data owner (DO) constantly transmits its data to a service provider (SP), together with additional authentication information. Clients register continuous range queries to the SP. Whenever the data change, the SP must update the results of all affected queries and inform the clients accordingly. The clients can verify the correctness of the results using the authentication information provided by the DO. Compared to conventional databases, stream environments pose new challenges 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 updates. We face these challenges through several contributions. Since there is no previous work, we first present a technique, called REF, that achieves correctness and temporal completeness but incurs false transmissions, i.e., the SP has to inform clients whenever there is a data update, even if their results are not affected. Then, we propose CADS, which minimizes the processing and transmission overhead through an elaborate indexing scheme and a virtual caching mechanism. Finally, we extend CADS to the case where multiple owners outsource their data to the same SP. The SP integrates all data in a single authentication process, independently of the number of DOs.
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Rights © ACM, 2007. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 33rd International Conference on Very Large Data Base, {23-27 September 2007, Vienna, Austria}
Language English
Format Conference paper
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