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Secure Content Store

Project description Documentation Status

What it is

seccs is a Python library that realizes a secure and efficient hash-table-like data structure for contents on top of any existing key-value store as provided by, e.g., cloud storage providers.

It has been developed as part of the work [LS17] at CISPA, Saarland University.


$ pip install seccs

If you want to use AES-SIV encryption (you probably want!), you also need to install PyCrypto 2.7a1 which is not yet available in PyPI:

$ pip install

Usage and Overview

seccs is a Python implementation of sec-cs, a secure and efficient hash-table-like data structure for contents. It stores its data on top of any existing database providing a key-value store interface. Thus, it is likewise usable with in-memory dict objects, persistent databases like ZODB, and many cloud storage providers.

Its details are described in [LS17]. In short, it is suitable for usage on untrusted cloud storage and has the following desirable properties:

  • Confidentiality:

    Stored contents are securely encrypted using a symmetric key.

  • Authenticity:

    sec-cs guarantees authenticity of all stored contents, irrespective of gurantees of the underlying database.

  • Storage Efficiency:

    Data deduplication strategies are applied to all stored contents. When storing new contents, overlapping parts of existing contents are automatically reused as to avoid redundancy. sec-cs is optimized for efficiency in presence of many similar contents: Storage costs of an n-bytes content that differs only slightly from an existing content are in O(log n).

Typical Use Case

In the most-typical configuration, sec-cs chunks its contents hierarchically using ML-CDC (see [LS17]), usually relying on Rabin Karp hashes, and stores the resulting nodes in a database after applying AES-SIV-256 for encryption and authentication. From a user perspective, we have to initialize a suitable database object and a 32-bytes key first.

Database and key setup:
>>> database = dict()
>>> import os
>>> key = os.urandom(32)

Note that we might want to store the database and the key at some persistent location in practice.

Next, we need to create a crypto wrapper which is in charge of all the cryptographic operations. Depending on our security goals (e.g., whether encryption is required), we could choose any suitable wrapper from seccs.crypto_wrapper. Afterwards, we can instantiate the data structure.

Choice of crypto wrapper and instantiation of data structure:
>>> import seccs
>>> crypto_wrapper = seccs.crypto_wrapper.AES_SIV_256(key)  # install PyCrypto>=2.7a1 to use AES-SIV
>>> seccs = seccs.SecCSLite(256, database, crypto_wrapper)  # 256 is the chunk size
We can now insert contents…
>>> content = b"This is a test content."
>>> digest = seccs.put_content(content)
>>> repr(digest)
…retrieve them…
>>> seccs.get_content(digest)
This is a test content.
…and delete them as soon as they are not needed anymore:
>>> seccs.delete_content(digest)

Storage Efficiency

seccs avoids redundancy in the database wherever possible, as gets clear in the following example.

Consider this function for measuring the database’s current storage costs in bytes:
>>> import sys
>>> def dbsize(db):
>>>     return sum([sys.getsizeof(k) + sys.getsizeof(v) for (k, v) in db.items()])
Initially, the database is empty:
>>> dbsize(database)
Insertion of a 1 MiB content clearly causes some storage costs:
>>> content1 = os.urandom(1024*1024)
>>> digest1 = seccs.put_content(content1)
>>> dbsize(database)
But inserting the same content for a second time does not incur additional costs:
>>> content2 = content1
>>> digest2 = seccs.put_content(content2)
>>> digest1 == digest2  # identical contents yield identical digests
>>> dbsize(database)

Clearly, the database grows if different contents are inserted. However, these costs are low if inserted contents are similar to existing ones.

Only about 2.3 KiB are required to store another 1 MiB content with one byte changed:
>>> content3 = b''.join([content1[:512*1024], b'x', content1[512*1024+1:]])
>>> digest3 = seccs.put_content(content3)
>>> dbsize(database)
Costs are similar even if the identical parts are shifted…
>>> content4 = b''.join([content1[:512*1024], b'xyz', content1[512*1024+1:]])
>>> digest4 = seccs.put_content(content4)
>>> dbsize(database)
…and deduplication is also performed if a content consists of parts of different existing contents:
>>> content5 = b''.join([content1, content3, content4])
>>> digest5 = seccs.put_content(content5)
>>> dbsize(database)

In the last example, the growth was about 3 KiB.

Furthermore, storage space is reclaimed completely when contents are removed:
>>> seccs.delete_content(digest5)
>>> seccs.delete_content(digest4)
>>> seccs.delete_content(digest3)
>>> seccs.delete_content(digest2)
>>> dbsize(database)
>>> seccs.delete_content(digest1)
>>> dbsize(database)


seccs uses tox for testing, so simply run:

$ tox
[LS17] (1,2,3,4)

Dominik Leibenger and Christoph Sorge (2017). sec-cs: Getting the Most out of Untrusted Cloud Storage. In Proceedings of the 42nd IEEE Conference on Local Computer Networks (LCN 2017), 2017. (Preprint: arXiv:1606.03368)

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