Metadata-Version: 2.4
Name: traffic-taffy
Version: 0.9.8
Summary: A tool for doing differential analysis of pcap files
Project-URL: Homepage, https://traffic-taffy.github.io/
Author-email: Wes Hardaker <opensource@hardakers.net>
License-File: LICENSE.txt
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Requires-Dist: argparse-with-config>=0.1.4
Requires-Dist: cryptography
Requires-Dist: dnssplitter
Requires-Dist: dotnest>=1.0
Requires-Dist: dpkt
Requires-Dist: ip2asn>=1.6.6
Requires-Dist: msgpack
Requires-Dist: pandas
Requires-Dist: pcap-parallel
Requires-Dist: pyfsdb
Requires-Dist: pyopenssl==22.1.0
Requires-Dist: pyqt6-charts
Requires-Dist: rich
Requires-Dist: rich-argparse
Requires-Dist: scapy
Requires-Dist: seaborn
Description-Content-Type: text/markdown

# Traffic Analysis of Fluctuating Flows (TAFFy)

## About

Network and security operators are continually bombarded by strange
deviations in network traffic that are sometimes operationally
problematic, sometimes a threat to security, and other times just
plain odd.  Wouldn't it be wonderful to have a tool that accurately
tells you exactly what has changed in these traffic profiles?
This tool is designed to do just that.

## Installation

    pip install traffic-taffy

## Usage

See the online [readthedocs
documentation](https://traffic-taffy.readthedocs.io/).

## Development

Traffic-taffy is under very rapid development with a fair amount of
refactoring as time goes on into better class architectures.  If you
are considering looking at portions of the code and submitting pull
requests, please reach out to Wes ahead of time to check what changes
might be coming that will cause merge conflicts.

# Copyright and License

Traffic-taffy was created by [Wes Hardaker], a computer scientist at
[USC/ISI], with support from the Comcast Innovation Fund.

[Wes Hardaker]: https://ant.isi.edu/~hardaker/
[USC/ISI]: https://www.isi.edu/

This project is copyrighted by the University of Southern California,
Information Sciences institute.  It is released under the Apache 2.0
license.

# Acknowledgments

We greatly thank Comcast for this project was made possible through
their Comcast Innovation Fund.
