mlCommom

README.md

@@ -14,12 +14,9 @@ Additionally, PacketBreeze also categorizes packets into flows and shows a rich
 |:--:| 
 | *PacketBreeze takes packets and returns file with statistics of flows.* |
 
-| <img width="1559" alt="Packetbreeze-flowsClassification" src="assets/images/overall.png">
-|:--:|
-| *Packetbreeze takes packets and returns file with statistics of flows and classifies packets as benign or malicious.*  |
 
 
-| <img width="1559" alt="Packetbreeze-Confusion-Matrix" src="assets/images/confusion.png">
+| <img width="400" alt="Packetbreeze-Confusion-Matrix" src="assets/images/confusion.png">
 |:--:|
 | *Packetbreeze's output shown in a confusion matrix.*  |
 
@@ -29,17 +26,52 @@ Use PacketBreeze if you wish to build and operate machine-learning models on net
 
 ## 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.
+Thank you for using PacketBreeze
 
- * 
-
-## Support
+Community contributions are always welcome through GitHub Issues and Pull Requests.
+
+
+
+## Developers
+
+ Arman Singh Kshatri `221020412`
+ Swastika Satya	`221020453`