Privacy-Preserving Stream Aggregation with Fault Tolerance View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2012

AUTHORS

T. -H. Hubert Chan , Elaine Shi , Dawn Song

ABSTRACT

We consider applications where an untrusted aggregator would like to collect privacy sensitive data from users, and compute aggregate statistics periodically. For example, imagine a smart grid operator who wishes to aggregate the total power consumption of a neighborhood every ten minutes; or a market researcher who wishes to track the fraction of population watching ESPN on an hourly basis.We design novel mechanisms that allow an aggregator to accurately estimate such statistics, while offering provable guarantees of user privacy against the untrusted aggregator. Our constructions are resilient to user failure and compromise, and can efficiently support dynamic joins and leaves. Our constructions also exemplify the clear advantage of combining applied cryptography and differential privacy techniques. More... »

PAGES

200-214

Book

TITLE

Financial Cryptography and Data Security

ISBN

978-3-642-32945-6
978-3-642-32946-3

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-32946-3_15

DOI

http://dx.doi.org/10.1007/978-3-642-32946-3_15

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017902465


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