Real-Time Multi-Class Cyber-Attack Dataset

This dataset was created in a controlled real-time environment to collect different types of cyber-attack traffic.
The attacker machine used Kali Linux, and the target machine used Microsoft Windows with ownCloud running as the main server.

Four types of attacks were performed:

Reconnaissance: Using Nmap to scan and find open ports and services.

Brute Force: Using Hydra to try multiple username and password combinations.

DDoS: Using Slowloris to overload the server by sending many incomplete requests.

Data Exfiltration: Transferring unknown files from the attacker system to the victims system.

This dataset can be used for multi-class Cyber attack detection system.

The Dataset contains 12 Features timestamp,total_packets,total_streams,unique_src_ips,top_src_ip,top_src_ip_count,total_bytes,
avg_pkt_len,syn_count,fin_count,rst_count,http_requests