hi

i have a project as attached below.

any reference or guide on it?

thanks

In this project, you'll have to build your own network which has at least 2 clients (Malicious & Benign) and 4 services (DNS server, Web server, Secure Web Server, Email server, File Server, FTP Server, DB server) on Mininet. 1. 2. Normal and benign communication between these clients and servers must be scripted and all traffic collected through TCPDUMP or Wireshark. At least 4 kinds of attacks must be implemented (for instance Bruteforce, SQL, XSS, Phishing, Probe, Infiltration/Trojan, Mitm, DOS/DDOS) and run from the malicious client. The attack traffic must also be captured. 3. 4. Using a feature generator tool (like CICFlowmeter) or any other similar tool, the network capture data (PCAP) has to be converted into a labelled dataset (binary 0/1 or multiclass Using the dataset, perform feature ranking to choose some of the most important features and run different ML models (148, MLP, SVM, RNN, Naive Bayes) to test their efficiency 5. Recommend one of the models and build a live detection tool using Python to detect network anomalies. You can choose whether it's real-time detection or offline detection. 6. 7. The accuracy of your detection tool also needs to be tested on non-learned attacks (potentially zero-day attacks). 8. Rubric Network Topology (7) Attack variety (7) Feature Generation (6) ML model Comparison (8) Detection Tool (12) Zero-day detection (6)