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- W2016317680 abstract "In this paper, we focus on the problem of data privacy on the cloud, particularly on access controls over stream data. The nature of stream data and the complexity of sharing data make access control a more challenging issue than in traditional archival databases. We present Streamforce -- a system allowing data owners to securely outsource their data to an untrusted (curious-but-honest) cloud. The owner specifies fine-grained policies which are enforced by the cloud. The latter performs most of the heavy computations, while learning nothing about the data content. To this end, we employ a number of encryption schemes, including deterministic encryption, proxy-based attribute based encryption and sliding-window encryption. In Streamforce, access control policies are modeled as secure continuous queries, which entails minimal changes to existing stream processing engines, and allows for easy expression of a wide-range of policies. In particular, Streamforce comes with a number of secure query operators including Map, Filter, Join and Aggregate. Finally, we implement Streamforce over an open-source stream processing engine (Esper) and evaluate its performance on a cloud platform. The results demonstrate practical performance for many real-world applications, and although the security overhead is visible, Streamforce is highly scalable." @default.
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- W2016317680 date "2014-03-03" @default.
- W2016317680 modified "2023-09-27" @default.
- W2016317680 title "Streamforce" @default.
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- W2016317680 doi "https://doi.org/10.1145/2557547.2557556" @default.
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