Security and Deduplication in the Cloud Danny Harnik - IBM Haifa Research Labs.
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Transcript of Security and Deduplication in the Cloud Danny Harnik - IBM Haifa Research Labs.
Security and Deduplication in the Cloud
Danny Harnik - IBM Haifa Research Labs
What is Deduplication Deduplication: storing only a single copy of redundant data
Applied at the file or block level
Major savings in backup environments (saves more than 90% in common business scenarios)
“most impactful storage technology” April 2008: IBM acquires Dilligent July 2009: EMC acquires DataDomain July 2010: DELL acquires Ocarina
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How are files deduped? Fingerprint each file using a hash function
Common hashes used: Sha1, Sha256, others… Store an index of all the hashes already in the system
New file: Compute hash Look hash up in index table If new → add to index If known hash → store as pointer to existing data
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Client-side deduplication Save bandwidth as well as storage.
Also know as “source-based dedupe” or “WAN deduplication”
Client computes hash and sends to server If new → server requests client for the file (upload data) Otherwise (dedupe) → skip upload and register the client as
another owner of the file
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Client
Let it be.mp3
hash
2fd4e1
Server
2fd4e1
Index
2fd4e1
Let it be.mp3
Deduplication and privacy Our attacks are relevant to the following setting:
Client-side deduplication Cross-user deduplication
If two or more users store the same file, only a single copy is stored.
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Cloud storage and deduplication Cloud storage services are gaining popularity
Online file backup and synchronization is huge Lots to gain from deduplication
Use/used cross-user client-side deduplication Mozy Dropbox Memopal …
MP3Tunes
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Deduplication and privacy I Harnik, Pinkas & Shulman-Peleg,
IEEE Journal of Security and Privacy, Vol 8. 2010
Client learns if an object is already in system A narrow “peep hole” to contents of other users
Discussed attacks and partial solutions Illegal content searching “Salary attack” Covert channel
Several ways to prevent: Encrypt or dedupe server side only Dedupe only on long files Noisy dedupe…
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Deduplication and privacy II Halevi, Harnik, Pinkas & Shulman-Peleg,
ACM CCS 2011
A more direct attack Starting point: Suppose I get the hash value of your file…
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The attack Attacker obtains hash of victim’s file Signs up for the service with own account Attempts to upload a file, but swaps the hash value with
that of the victim’s file.
File is now registered to attacker Download file…
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Client
Any file
hash
e3b890
Server
2fd4e1
Index
2fd4e1
Let it be.mp3
2fd4e1
Obtaining the hash
1. Hash used for other services Hash does not reveal “anything” on the file – not meant to be secret
2. Malicious software Easier to send a small signature undetected Also true for break-in at the server side
3. CDN attack Alice sends all her friends the hash of a movie
Friends can download it from the server Server essentially serves as a Content Distribution Network (CDN).
Might break its cost structure, if it planned on serving only a few restore ops.
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Swapping the hash [Dorrendorf & Pinkas 2011]
Implemented the attacks against two major storage servers One services uses SHA256 to identify files Another uses a 160 bit hash value which was not identified
Dropship (April, 2011) implementation of the CDN over dropbox “written in Python. Allow you to download to your Dropbox any
file, which description we got in JSON format (similar as description propagated in .torrent files).”
[Mulazzani, Schrittwieser, Leithner, Huber & Weippl 2011] Implemented the attack on Dropbox In Usenix Security 2011
A non-issue in upcoming cloud storage standards 11
SOLUTIONS !
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Naïve Solutions
Use a non-standard hash (e.g. Hash(“service name” | file) ) But all clients must know hash function Irrelevant in most scenarios (CDN/malicious software etc..)
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Better naïve Solutions
Use a challenge-response phase For every upload, server picks a random nonce, and
asks client to compute Hash( nonce | file ) This requires client to have the file But the server, too, must now retrieve the file from secondary
storage, and compute the hash
Alternative: Pre-compute Hash( nonce | file) and store together with hash Back to root cause of problem: short hash represents file
entirely.
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Proofs of Ownership (POWs)
Server preprocesses the file Stores some short information per file (few bytes only)
Proof stage: a challenge response – done only during file upload Honest client has access to the file Server has only access to preprocessed information. cannot retrieve files
from secondary storage. Must be bandwidth efficient Client computation should be efficient (time & memory)
Security definition: Malicious client may have: Partial knowledge of file (file has k min-entropy to it) May receive additional information from accomplices (m bits)
If k – m > security parameter, then proof fails whp.
15filePrior knowledge kAccomplice data
s
Proofs of Retrievability (PORs) Role reversal: Server proves to client that it actually store its file
Strong extraction based definition (we use a relaxed notion) State of the art solutions all send a pre-processed file to the server.
E.g. [NR05],[JK07],[SW08],[DVW09] Cannot be done in our setting
In general, POR without preprocessing is a good POW Our first solution is a Merkle tree based POR
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Solution – first attempt
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File
Merkle Tree
Solution – first attempt
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File
Merkle Tree
Preprocessing: server stores root of tree
Solution – first attempt
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File
Merkle Tree
Proof: server asks client to present paths to t random leaves
A client which knows only a p fraction of the file, succeeds with prob < pt.
√ very efficient
Problem and solution Does not suffice when min-entropy is low (e.g. 90% of the file) Solution: Apply tree to an erasure coding of the file Satisfies security of POW and POR.
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FileErasure code
Merkle TreeMerkle Tree
Efficient encoding? Must pay either:
Large memory Multiple disk accesses
Bad for large files
Protocols with small space Limit solution to use an L byte buffer for all the
computation For example: L=64MB
Relax security guarantees: Can only tolerate L bytes of accomplice data.
2323
filePrior knowledge Accomplice
sL
Second protocol: hash to small space
First hash file to a buffer of L bytes. Then construct Merkle-tree over the buffer.
Reducer: use pairwise-independent hashing
Security: POW will fail (w.h.p.) adversary that Has at least k bits min-entropy on the file Receives less than Min(L, k-s) bits
from an accomplice
24File
Reduced file
Merkle Tree
Reducer
Is this efficient enough ? Still not really practical
File size M Buffer size L Reducer requires Ω(M·L) time
We want to push it further down…
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Third protocol: Reduce and Mix
In Reducer: XOR each block to a constant number of random locations Runs in O(M+L) time
Add a mixing phase
26File
Reduced file
Merkle Tree
Reducer
Reduced & mixed file
Mixer
Hypothesis: reduce + mix forms a good code
Security defined against a generalized block fixing source distribution
Performance of the different phases of the low space PoW
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When is it worth the effort?
Summary Identified security implications of client-side deduplication
Introduced POWs to enable client-side deduplication in the cloud The challenge: offer meaningful privacy guarantees with a limited
toll on the resources
2929
Merkle Tree
Mixer
Reducer