xtrace_sdk.crypto.goldwasser_micali_client
==========================================

.. py:module:: xtrace_sdk.crypto.goldwasser_micali_client


Classes
-------

.. autoapisummary::

   xtrace_sdk.crypto.goldwasser_micali_client.GoldwasserMicaliClient


Module Contents
---------------

.. py:class:: GoldwasserMicaliClient(chunk_num = 2, embd_len = 512, key_len = 1024)

   Bases: :py:obj:`xtrace_sdk.crypto.hamming_client_base.HammingClientBase`


   This is an implementation of goldwasser micali cryptography system optimized for calculating hamming distance between
   two binary vectors.


   .. py:attribute:: keys


   .. py:attribute:: embd_len
      :value: 512



   .. py:attribute:: chunk_num
      :value: 2



   .. py:attribute:: chunk_len
      :value: 512



   .. py:method:: serial_pk()

      serialzation of public key for networking/storage purpose

      :return: serialized pk
      :rtype: bytes



   .. py:method:: serial_sk()

      serialzation of secret key for networking/storage purpose

      :return: serialized sk
      :rtype: bytes



   .. py:method:: dump_pk(file_path)

      saves publick key to disk

      :param file_path: the path to which public key will be saved on disk
      :type file_path: str



   .. py:method:: dump_sk(file_path)

      saves secret key to disk

      :param file_path: the path to which secret key will be saved on disk
      :type file_path: str



   .. py:method:: id2power(id_)

      helper: return chunk id & corresponding power of 2 given an id in the original padded arr

      :param id_: id_ of an entry in an embedding vector
      :type id_: int



   .. py:method:: encrypt(embd)

      This function implements the encryption scheme on embedding vectors that needs to be run on client side.

      :param embd: the embedding vector to be encrypted
      :type embd: iterable[0,1]
      :return: return a list of length chunk_num contaning Goldwasser_MicaliEncryptedNumber
      :rtype: list[Goldwasser_MicaliEncryptedNumber]



   .. py:method:: encode_hamming_client(ct1, ct2)

      This function is called from client side.

      :param embd1: ciphertext of embedding 1
      :type embd1: Goldwasser_MicaliEncryptedNumber
      :param embd2: ciphertext of embedding 2
      :type embd2: Goldwasser_MicaliEncryptedNumber
      :return: return a list of length chunk_num contaning large int
      :rtype: Goldwasser_MicaliEncryptedNumber



   .. py:method:: encode_hamming_server(ct1, ct2, pk)
      :staticmethod:


      This function is called from server side.

      :param ct1: ciphertext of embedding 1
      :type ct1: Goldwasser_MicaliEncryptedNumber
      :param ct2: ciphertext of embedding 2
      :type ct2: Goldwasser_MicaliEncryptedNumber
      :param pk: public key
      :type pk: Goldwasser_MicaliEncryptedNumber
      :return: return a list of length chunk_num contaning large int
      :rtype: Goldwasser_MicaliEncryptedNumber



   .. py:method:: decode_hamming_client(cipher)

      Given a Goldwasser_MicaliEncryptedNumber returned from server, calculate the hamming distance encoded

      :param cipher: a cipher regturned by server which encodes the hamming distance between two encrypted embeddings
      :type cipher: Goldwasser_MicaliEncryptedNumber
      :return: hamming distance encoded by cipher
      :rtype: int