NOISE was written in July of 2013 as a way to create “real-looking” text based upon a collection of reference texts, which can then be used in emails, web searches, IRC chats, or any other medium you can think of that makes it a bit too easy to profile an individual’s communication habits. Currently, NOISE only has email and Twitter dispatchers for generated texts.
|NOISE-0.4.tar.gz (sha256)||0.4||17 August 2013||31KB|
How does it work?
You give NOISE one or more texts to use as a reference. The more texts, and longer texts, the better. NOISE then uses this collection of reference texts, called a corpus, to generate new, “real-looking” text, using an algorithm called a “Markov Chain”. If you provide an optional set of keywords you want used in the generated text, NOISE will then replace any proper nouns in the generated text with a random selection of keywords from your list. NOISE will then email these generated texts to recipients of your choice, on a periodic but somewhat random schedule.
NOISE requires python version 2.7, the NumPy library, and the Natural Language Toolkit. See their websites for installation instructions:
- Python: http://python.org/download/
- NumPy: http://www.scipy.org/install.html
- NLTK: http://nltk.org/install.html (Requires
maxent_treebank_pos_taggerfrom NLTK Data)
For Debian-based systems, dependencies can be installed as follows:
$ sudo apt-get update && sudo apt-get install python2.7 python-pip $ sudo pip install numpy nltk $ python -m nltk.downloader maxent_treebank_pos_tagger
How to use
NOISE currently comes with four different programs, which can all be run on their own:
- noise.py: This is the main NOISE program, which uses noise_generate, noise_dispatch, and noise_tweet. It reads in a configuration file as its only parameter. This is probably what you’ll want to run.
- noise_generate.py: This takes a collection of reference texts (called a “corpus”), and generates “real-looking” text based upon the corpus using Markov chains.
- noise_dispatch.py: The dispatcher simply connects to a mail server and sends an email based on the given parameters.
- noise_tweet.py: This program will tweet something on Twitter…
- noise_keyword_parser.py: This program takes lists of keywords as input and creates a weighted keywords file, to be used in noise.py or noise_generate.py.
NOISE comes with a default configuration file
noise.default.conf that you can modify to meet your needs, and also has explanations of all the relevant options. NOISE can then be run as so:
$ python noise.py -c noise.conf
$ torsocks python noise.py -c noise.conf
NOTE: Tor does not provide perfect anonymity. Please see their full list of warnings before using Tor. Obviously, don’t use a personally identifiable email address with NOISE if you want to stay anonymous.
Corpus & Keywords
It’s up to you to provide your own corpus and keywords file. NLTK.org ships with some corpora you can use for free (see http://nltk.org/data.html).
Credits & License
NOISE is GPLv3 licensed. See LICENSE.txt
NOISE was created by Dan Staples (dismantl): http://disman.tl/ / email@example.com.
The Markov code comes from https://code.google.com/p/kartoffelsalad/.
SOCKS proxy functionality from https://code.google.com/p/socksipy-branch/.
28 July 2013: Initial release.
30 July 2013: Added recurring dispatch schedule and more documentation.
4 August 2013: noise.py can now generate fake PGP-encrypted emails.
9 August 2013: Added STARTTLS, new config option, misc bug fix
13 August 2013: Performance improvements, misc bug fixes, added min-keywords option
17 August 2013: Major code refactoring, added Twitter dispatcher, misc fixes