DDoS Attack Detection systems in Software Defined Networking

2018 COE Engineering Design Project (BM04)

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Faculty Lab Coordinator

Bobby Ma

Topic Category

Distributed / Cloud Computing

Preamble

Software Defined Networking (SDN) is an emerging network technology and is used extensively in cloud computing infrastructure. In SDN, a centralized controller is used to control data flows and manage network policy. Distributed Denial of Service (DDoS) attack is the most popular type of network attacks to disable network services. In this project, students will learn the structure of SDN and implement two types of DDoS attack detection systems in the SDN controller.

Objective

To implement two types of DDoS attack detection systems in the SDN platform. The first is based on statistical measurements while the second on machine learning. Their performances are also compared.

Partial Specifications

1. Study the concepts of SDN, DDoS, statistical measurement and machine learning.
2. Use the OpenDayLight Controller and Mininet to set up a SDN network.
3. Use Hping3 or other open-source attacking tools to generate attack traffic.

Suggested Approach

The project has three stages. In the first stage, students will set up a SDN network using OpenDayLight Controller and Mininet. In the second stage, students will learn how to program the controller to control the traffic flow in the SDN network. In the third stage, a statistical-based and machine-learning-based DDoS detection systems will be studied, implemented and tested.

Group Responsibilities

It is expected that all the members of the group are involved in the research, development and implementation of the project.

Student A Responsibilities

1. Study and understand the concepts of SDN, DDoS attack, statistical measurement and Machine Learning. 2. Setup a SDN network 3. Implement a statistical-based and Machine-learning-based DDoS attack detection systems in SDN by programming the SDN controller. 4. Evaluate the detection systems based on the detection performances.

Student B Responsibilities

1. Study and understand the concepts of SDN, DDoS attack, statistical measurement and Machine Learning. 2. Setup a SDN network 3. Implement a statistical-based and Machine-learning-based DDoS attack detection systems in SDN by programming the SDN controller. 4. Evaluate the detection systems based on the detection performances.

Student C Responsibilities

1. Study and understand the concepts of SDN, DDoS attack, statistical measurement and Machine Learning. 2. Setup a SDN network 3. Implement a statistical-based and Machine-learning-based DDoS attack detection systems in SDN by programming the SDN controller. 4. Evaluate the detection systems based on the detection performances.

Course Co-requisites

COE 768