15/05/2023: Last Lesson and Project Assignement (For those who will take the oral exam for the lab, attendance is required!)

Lesson Zoom Link: https://uniroma1.zoom.us/j/6086056923

In this repository you will find all lectures and scripts related to the NBD Course of 22/23

This course is composed by three main parts:

1. Using Wireshark to sniff packets and observe packet information

**macOS advice (command line execution):

  #Open your prompt
  
  sudo vi /etc/paths
  
  #Add your Path where Wireshark application is saved. (Following command is my own situation, just check under Applications)
  
  /Applications/Wireshark.app/Contents/MacOS/
  
  :wq
  
  #Close the prompt. Reopen it and check the execution of wireshark or t-shark commands

2. pcap reading:

   2.a) Reading a pcap file by python, extracting info and splitting it. Reading part ca be divided into sequential or parallel.

   2.b) Create the Dataframe from a starting pcap, analyzing different statistics from flow-based to Geographical referentiation IP addresses

3. Machine Learning (ML) Problem from scratch --> Classification field:

   3.a) Supervised Learning: D. Rossi, S. Valenti - ”Fine-grained traffic classification with Netflow data” (2010)

   3.b)Unsupervised Learning: Y. Zeng, T.M. Chen - ” Classification of Traffic Flows into QoS Classes by Unsupervised Learning and KNN Clustering” (2009)

At the end will be assigned the final project, you will work in group based on the team used during the course with the other Professors.

Project: The project can be divided into 2 main parts:

1. Statistical analysis: you will receive a trace from https://mawi.wide.ad.jp/mawi/ , we ask you to replicate the analysis observed during the lecture and maybe add something new (e.g. possible graph representation).

2. ML problem: choose to replicate or (3.a) or (3.b) from Lecture 3 on the mawi dataset.

Deadline:By July

Group composition: Please, fill the Excel file at this link https://docs.google.com/spreadsheets/d/1j_uFCVRob_ztTos5q0N1r_YiOEXGARsB/edit#gid=310448381

<IMPORTANT!!!>

Submission Guidelines: You have to send an email to me and Professor Cianfrani, attaching the presentation for your oral exam and your code in .py (or if you prefer .ipynb); at least 3 days before the oral exam. The date of the oral exam will then be confirmed by the Professor Cianfrani.