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PacketBreeze/README.md
2023-06-19 20:50:45 +05:30

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# PacketBreeze
PacketBreeze is an utility tool built for analysing and classifing packets by looking at packet headers.
## Primary design goals:
PacketBreeze aims to:
- **Classify packets and flows as benign or malicious with high true positives (TP) and low false positives (FP)**.
- **Use the labeled data to reduce amount of traffic requiring deeper analysis**.
Additionally, PacketBreeze also categorizes packets into flows and shows a rich ensemble of flow data and statistics.
| <img width="1559" alt="Packetbreeze-flows" src="assets/images/packetbreeze.png"> |
|:--:|
| *PacketBreeze takes packets and returns file with statistics of flows.* |
| <img width="400" alt="Packetbreeze-Confusion-Matrix" src="assets/images/confusion.png">
|:--:|
| *Packetbreeze's output shown in a confusion matrix.* |
## When to use Packetbreeze
Use PacketBreeze if you wish to build and operate machine-learning models on network packet data.
## Quick Start
Start by cloning the project: [link](https://git.weirdnatto.in/Unic-X/PacketBreeze.git)
Build the binary:
```console
foo@bar:~$ go build -o packetbreeze
```
Run the Binary:
```console
foo@bar:~$ ./packetbreeze -ifLiveCapture=true -fname=webgoat -maxNumPackets=40000000 -ifLocalIPKnown false
```
<p>
<em>Offline analysis of the PCAP packets</em>
</p>
---
### Requirements
Go
Python Requirements in [File](assets/requirements.txt)
## Who uses PacketBreeze?
* One can use PacketBreeze to label the network packets using ML before deep analysis. Thus resulting in faster analysis overall.
* Overall the target users for this project are intermediate network analyst, and network engineers.
## Get in touch
Thank you for using PacketBreeze
Community contributions are always welcome through GitHub Issues and Pull Requests.
## Developers
Arman Singh Kshatri `221020412`
Swastika Satya `221020453`