@hackage data-dispersal1.0.0.0
Space-efficient and privacy-preserving data dispersal algorithms.
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LGPL-2.1-only
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peter.robinson@monoid.at
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@hackage/acme-everything
This library provides space-efficient (m,n)-information dispersal algorithms (IDAs).
Given a ByteString bstr of length D, we encode bstr as a list fs of n
Fragments, each containing a ByteString
of length O(D/m). Then, each fragment in fs could be stored on a separate
machine for fault-tolerance.
Even if up to n-m of these machines crash, we can still reconstruct the original
ByteString out of the remaining m fragments.
The total space required for the n fragments is O((n/m)*D).
Note that m and n are roughly in the same order, so the actual storage overhead
for getting good fault-tolerance increases only by a constant factor.
The module Data.IDA contains the basic information dispersal algorithm. The module
Crypto.IDA augments the dispersal scheme by combining it with secret sharing, i.e.,
the knowledge of up to m-1 fragments does not leak any information about
the original data. See Crypto.IDA for details.
GHCi Example:
> :m + Data.IDA > let msg = Data.ByteString.Char8.pack "my really important data" > let fragments = encode 5 15 msg -- Now we could distributed the fragments on different sites to add some -- fault-tolerance. > let frags' = drop 5 $ take 10 fragments -- let's pretend that 10 machines crashed > decode frags' "my really important data"
Fault-Tolerance:
Suppose that we have N machines and encode our data as 2log(N) fragments
with reconstruction threshold m = log(N).
Let's assume that we store each fragment on a separate machine and each
machine fails (independently) with probability at most 0.5.
What is the probability of our data being safe?
Pr[ at most n-m machines crash ] >= 1-0.5^(log(N)) = 1-N^(-1).What is the overhead in terms of space that we pay for this level of fault-tolerance? We have n fragments, each of size D/m, so the total space is
n * D/ m = 2D.In other words, we can guarantee that the data survives with high probability by increasing the required space by a constant factor.
This library is based on the following works:
"Efficient Dispersal of Information for Security, Load Balancing, and Fault Tolerance", by Michael O. Rabin, JACM 1989.
"How to share a secret." by Adi Shamir. In Communications of the ACM 22 (11): 612–613, 1979.
"Secret Sharing Made Short" Hugo Krawczyk. CRYPTO 1993: 136-146