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https://github.com/jkawamoto/psi-dlpa
Distributed Laplace Perturbation Algorithm
https://github.com/jkawamoto/psi-dlpa
differential-equations paste privacy sigmod
Last synced: 13 days ago
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Distributed Laplace Perturbation Algorithm
- Host: GitHub
- URL: https://github.com/jkawamoto/psi-dlpa
- Owner: jkawamoto
- License: gpl-3.0
- Created: 2017-03-09T16:11:27.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-10-26T02:55:28.000Z (about 7 years ago)
- Last Synced: 2024-10-04T17:08:59.784Z (about 1 month ago)
- Topics: differential-equations, paste, privacy, sigmod
- Language: Python
- Homepage: https://jkawamoto.github.io/psi-dlpa/
- Size: 3.64 MB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: COPYING
Awesome Lists containing this project
README
# Distributed Laplace Perturbation Algorithm
[](https://www.gnu.org/copyleft/gpl.html)
[](https://travis-ci.org/jkawamoto/psi-dlpa)
[](https://app.wercker.com/project/byKey/e2799a5e4bf381734ac6d2d5dc844f3e)
[](https://github.com/jkawamoto/psi-dlpa/releases/tag/0.3.0)
Client and server applications providing Distributed Laplace Perturbation
Algorithm (DLPA).
The DLPA has been introduced by
[Vibhor Rastogi](https://www.linkedin.com/in/vibhor-rastogi-6b680152)
and [Suman Nath](https://www.microsoft.com/en-us/research/people/sumann/)
in "[Differentially Private Aggregation of Distributed Time-Series with
Transformation and Encryption](http://dl.acm.org/citation.cfm?id=1807247),"
and published in [SIGMOD 2010](http://www.sigmod2010.org/index.shtml).
## Client
This package has client class `dlpa.DLPAClient`.
To create an instance, the constructor takes two arguments:
* host: Address of a DLPA server,
* port: Port number of the DLPA server.
Although the client class implements several protocols defined in DLPA,
`get_key` and `encrypt_noisy_sum` are the only method users might have interest.
The `get_key` requests a client key to the server.
It takes one argument, client ID, and returns a client key object.
The other method `encrypt_noisy_sum` runs the Entryp-Noisy-Sum protocol,
which is the key protocol of DLPA.
It takes the following four arguments:
* ck: Client key.
* client_id: Client ID.
* value: Scalar or vector to be sent to the server by Encrypt-Sum
protocol.
* epsilon: Parameter to generate Laplace noises.
and returns a time slot when the request is attached.
## Server
`dlpa-server` command runs a server application of DLPA.
The following is the usage of this command:
```
usage: dlpa-server [-h] --port PORT --clients NCLIENT
[--max-workers MAX_WORKERS] [--key-length M_LENGTH]
[--time-span SPAN]
optional arguments:
-h, --help show this help message and exit
--port PORT Listening port number.
--clients NCLIENT The number of clients.
--max-workers MAX_WORKERS
The maximum number of workers (default: 10).
--key-length M_LENGTH
Bit length of the secret key (default: 2048).
--time-span SPAN Second of one time slot.
```
Note that the port number and the number of clients are necessary arguments.
You can also starts a server from another python script by using `dlpa.server`
function.
The function takes the following keyword arguments:
* port: Port number the created server listen.
* max_workers: The maximum number of workers.
* nclient: The number of clients connecting this server.
* m_length: Bit length of the secret key.
and returns a server object, which has a method `stop(t)` to stop the server
within the given time `t`.
Callers are responsible for calling the method to close the server.
## Installation
```
$ pip install --upgrade psi-dlpa
```
Additionaly, if you install [gmpy2](https://pypi.python.org/pypi/gmpy2),
computation time will be reduced.
To install gmpy2 in mac, you also need to install mpc, mpfr, and libmp.
Those three packages are available in [Homebrew](https://brew.sh/).
## License
This software is released under The GNU General Public License Version 3,
see [COPYING](COPYING) for more detail.
The functions, powmod, invert, and getprimeover, defined in `src/dlpa/util.py`
are made by Data61 | CSIRO and released under the GPLv3.
The original source code is
[here](https://github.com/n1analytics/python-paillier/blob/master/phe/util.py).