Paper 2015/739

Practical and Scalable Sharing of Encrypted Data in Cloud Storage with Key Aggregation

Hung Dang, Yun Long Chong, Francois Brun, and Ee-Chien Chang

Abstract

We study a sensor network setting in which samples are encrypted individually using different keys and maintained on a cloud storage. For large systems, e.g. those that generate several millions of samples per day, fine-grained sharing of encrypted samples is challenging. Existing solutions, such as Attribute-Based Encryption (ABE) and Key Aggregation Cryptosystem (KAC), can be utilized to address the challenge, but only to a certain extent. They are often computationally expensive and thus unlikely to operate at scale. We propose an algorithmic enhancement and two heuristics to improve KAC’s key reconstruction cost, while preserving its provable security. The improvement is particularly significant for range and down-sampling queries – accelerating the reconstruction cost from quadratic to linear running time. Experimental study shows that for queries of size 2^15 samples, the proposed fast reconstruction techniques speed-up the original KAC by at least 90 times on range and down-sampling queries, and by eight times on general (arbitrary) queries. It also shows that at the expense of splitting the query into 16 sub-queries and correspondingly issuing that number of different aggregated keys, reconstruction time can be reduced by 19 times. As such, the proposed techniques make KAC more applicable in practical scenarios such as sensor networks or the Internet of Things.

Metadata
Available format(s)
-- withdrawn --
Category
Applications
Publication info
Published elsewhere. IHMMSec 2016
DOI
http://dx.doi.org/10.1145/2909827.2930795
Keywords
key management
Contact author(s)
hungdang @ comp nus edu sg
History
2017-02-23: withdrawn
2015-07-24: received
See all versions
Short URL
https://ia.cr/2015/739
License
Creative Commons Attribution
CC BY
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