Support Vector Machine (SVM)


I am doing a research project for my Bachelor of IT (honours) on Machine Learning for Cloud Security.

This research paper discusses the Fraudulent Resource Consumption (FRC) Attack and uses Support Vector Machines (SVM) to detect cloud-based FRC attacks. Fraudulent Resource Consumption (FRC) attacks are created by slowly using cloud services’ metered resources. The attacker’s goal is to abuse the utility pricing model by stealing cloud resources. This skilful resource overuse results in a significant cost burden for the client. These assaults employ low-intensity HTTP requests per hour, like legitimate users. Due to this, FRC attacks are difficult to detect. FRC is an Economic Denial of Service (EDoS) attack that targets cloud adopters’ financial resources by increasing their costs. Unlike DDoS assaults, which can temporarily block legitimate users from accessing services, EDoS attacks can significantly increase cloud users’ costs. Support-vector machines (SVMs, also known as support-vector networks) are supervised learning models that examine data for classification and regression analysis. FRC attacks are low-level DoS attacks.

For this, I have set up a lab, we have used VMware Fusion version 12.2.1, and the host machine is Macbook Pro 32 GB RAM 1 TB SSD HDD. The operating system used is:

• Kali Linux – From where we launch the FRC attack

• Windows Server 2019 – This will be our webserver hosting a website.

• Windows XP or Windows 10 is the client machine we will try to access our website.

To perform network analysis before and after the attack, I installed Wireshark on Windows Server 2019.

Now I want guidance for a script that Can capture this generated FRC traffic, run SVM on it for training and then run SVM on it for testing. Training can be one script, and testing can be another


I shall be highly grateful if you could kindly guide me in this.

Thanks & regards,

Osama Faheem