Project information
- Title: From Ripple to Waves: DNS Amplification Attacks
- Category: Network Infrastructure
- Author: Andrea Alberti - Davide Ligari - Cristian Andreoli - Matteo Scardovi - Intini Karim
- Project date: 10 July, 2023
- Project URL: Github-DDoS_attack
DNS Amplification Attack
Simulation of a DNS Reflection and Amplification DDoS attack
About • Contributors • Folder Structure • Usage
About
The DNS Amplification Attack project aims to study and analyze the security implications of DNS amplification attacks. DNS amplification attacks exploit the inherent characteristics of the DNS protocol to overwhelm target servers with a large volume of traffic, causing disruptions in service availability.
The project investigates the effectiveness of various mitigation measures to protect against DNS amplification attacks. It explores proactive measures such as rate limiting and trusted sources, detection techniques such as routing hops detection and machine learning, and resilience measures such as anycast schemes and caching behavior modifications.
The repository provides detailed instructions for configuring the DNS server, relevant research papers, the project report, a presentation, scripts used to perform the attack and collect data, and the collected data itself for further analysis.
Contributors
Folder Structure
The repository is organized into the following folders:
- DNS Server Configurations: This folder contains instructions and configuration files for setting up the DNS server.
- Papers: This folder includes the research papers that were read and referred to during the project.
- Presentation: The presentation folder contains the slides and any additional materials used for presenting the project.
- Report: This folder contains the final report documenting the project, including its methodology, findings, and conclusions.
- Scripts: The scripts folder includes Python scripts used to perform the attack and Bash scripts used to collect data during the experiment.
- Data: This folder contains the collected data and Jupyter notebooks used for data analysis and visualization.
Usage
Each folder within the repository has its own specific purpose and contains relevant files. To access the desired information or resources, navigate to the respective folder and refer to the provided documentation.