Updated the main page's README file
# Poseidon: Machine Learning - Phase II
## Overview
-This repository contains the components necessary to build a docker container that can be used for training a number of ML models using network packet captures (pcaps). The repository includes scripts necessary to do the training (e.g. "train_OneLayer.py") as well as doing the evaluation once a model has been trained (e.g. "eval_OneLayer.py")
+Poseidon is a machine learning implementation of our quest to determine
+two questions: (1) what is on the network; and (2) what is it doing? For
+more background and context on our project, please check out
+[the Poseidon project](https://www.cyberreboot.org/projects/poseidon/)
+page on our website. This repo specifically covers the algorithms and
+models we deployed in the second phase of our research.
-While this repository and resulting docker container can be used completely independently, this code was written to support the Cyber Reboot Vent and Poseidon projects. See:
+While this repository and resulting docker container can be used completely
+independently, the code was written to support the Cyber Reboot Vent and
+Poseidon projects. See:
[Vent](https://github.com/CyberReboot/vent) plugins for evaluating
machine learning models on network data as part of the
[Poseidon](https://github.com/CyberReboot/poseidon) SDN project.
+This repository contains the components necessary to build a docker container
+that can be used for training a number of ML models using network packet
+captures (pcaps). The repository includes scripts necessary to do the
+training (e.g. "train_OneLayer.py") as well as doing the evaluation once a
+model has been trained (e.g. "eval_OneLayer.py")
+
+Additional algorithms and models will be added here as we delve more
+deeply into network security profiles via machine learning models. Feel
+free to use, discuss, and contribute!
+
+
## Plugins
-The current supported plugins are:
-BLAH
+The plugin (i.e., model) we currently have available is **DeviceClassifier**,
+which utilizes the Random Forest technique by default, but the One Layer
+feedforward technique we had used in the Poseidon project is also included.
+
+For more information, check out the respective README file included within
+each plugin's folder.
+
+
+# Installation/Run
+
+Our models can be executed via Vent, Docker, and standalone. We recommend
+deployment via Vent in conjunction with Poseidon if you are running an SDN
+(software-defined network). Otherwise, we recommend using Docker.
+
+See the respective README files included in the plugin's folder for
+instructions on deployment.
