pyope 0.2.2

Quick examples

Quick start

from pyope.ope import OPE
random_key = OPE.generate_key()
cipher = OPE(random_key)
assert cipher.encrypt(1000) < cipher.encrypt(2000) < cipher.encrypt(3000)
assert cipher.decrypt(cipher.encrypt(1337)) == 1337

You can specify input and output ranges. Otherwise, default input (0..2^15-1) and output (0..2^31-1) ranges are used.

from pyope.ope import OPE, ValueRange
cipher = OPE(b'long key' * 2, in_range=ValueRange(-100, 100),
                              out_range=ValueRange(0, 9999))
assert 0 < cipher.encrypt(10) < cipher.encrypt(42) < 9999

About order-preserving encryption

Order-preserving encryption (OPE) allows to compare ciphertext values in order to learn the corresponding relation between the underlying plaintexts. By definition, order-preserving encryption methods are less secure than conventional encryption algorithms for the same data sizes, because the former leak ordering information of the plaintext values.

How can OPE be useful? For example, some systems may need OPE to perform a certain set of queries (such as range SQL queries) over encrypted data. These systems include CryptDB and Monomi to name a few.

Security

As mentioned above, security guarantees for Boldyreva’s schema are weaker than those of deterministic encryption schemes, but security can still be improved if the encryption keys are long enough. It is advised to use randomly generated keys at least 256 bits long.

Running tests

PyTest is used as a test framework. Run all tests:

$ py.test tests/

TODO

• More tests

• Optimize performance

• Security guarantees?

0.1.0 (2017-01-01)

• Use ‘cryptography’ instead of ‘pycrypto’