Foundations and Trends (R) in Databases
1 total work
Secure Distributed Data Aggregation
by Haowen Chan, Hsu-Chun Hsiao, Adrian Perrig, and Dawn Song
Published 30 June 2011
Secure Distributed Data Aggregation surveys the various families of approaches to secure aggregation in distributed networks such as sensor networks. It focuses on the important algorithmic features of each approach, and provides an overview of a family of secure aggregation protocols which use resilient distributed estimation to retrieve an approximate query result that is guaranteed to be resistant against malicious tampering. It then covers a second family, the commitment-based techniques, in which the query result is exact but the chance of detecting malicious computation tampering is probabilistic. Finally, it describes a hash-tree based approach that can both give an exact query result and is fully resistant against malicious computation tampering.
In its selection of covered literature, this book sets out to provide the reader with a general intuitive understanding of the field, rather than to bring the reader exhaustively up to date with all algorithms for the area. It adopts a tutorial approach, selecting the publications that most clearly exemplify a certain class of approaches (or which have been most influential historically), rather than focusing on breadth or depth of coverage in terms of the most effective or the most recent algorithms.
In its selection of covered literature, this book sets out to provide the reader with a general intuitive understanding of the field, rather than to bring the reader exhaustively up to date with all algorithms for the area. It adopts a tutorial approach, selecting the publications that most clearly exemplify a certain class of approaches (or which have been most influential historically), rather than focusing on breadth or depth of coverage in terms of the most effective or the most recent algorithms.