We revisit the problem of privacy-preserving range search and sort
queries on encrypted data in the face of an untrusted data store.
Our new protocol RASP has several advantages over existing work.
First, RASP strengthens privacy by ensuring {forward security}:
after a query for range $[a,b]$, any new record added to the data
store is indistinguishable from random, even if the new record falls
within range $[a,b]$. We are able to accomplish this
using only traditional hash and block cipher operations, abstaining
from expensive asymmetric cryptography and bilinear pairings.
Consequently, RASP is highly practical, even for large database
sizes. Additionally, we require only cloud {storage} and not a
computational cloud like related works, which can reduce monetary
costs significantly. At the heart of RASP, we develop a new
{update-oblivious} bucket-based data structure. We allow for
data to be added to buckets without leaking into which bucket it has
been added. As long as a bucket is not explicitly queried, the data
store does not learn anything about bucket contents. Furthermore, no
information is leaked about data additions following a
query. Besides formally proving RASP's privacy, we also present a
practical evaluation of RASP on Amazon Dynamo, demonstrating its
efficiency and real world applicability.
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