Serial Number: 83
Year: 2020
Kind of Traffic: Real
Publicly Available: Yes
Count of Records: 1GB
Features Count: 12
No. of citations: 353
Attack Type: Backdoor, Benign, Bot, Brute Force, DoS , etc
Download Links: https://www.kaggle.com/datasets/dhoogla/nfuqnids
Abstract: Sarhan et.al presented dataset NF-UQ-NIDS. The NF-UQ-NIDS dataset is a comprehensive amalgamation of four prominent network intrusion detection datasets: BoT-IoT, UNSW-NB15, CSE-CIC-IDS2018 and ToN-IoT consolidated within the NF-collection by the University of Queensland. This unified dataset aims to standardize network-security datasets, enabling interoperability and facilitating larger-scale analyses. It incorporates an extra label attribute that identifies the source dataset of each flow, allowing comparison across different testbed networks. Attack categories have been consolidated for clarity, with specific attacks grouped under parent categories such as DoS, DDoS, brute-force, and injection attacks. The dataset featuring a diverse range of attack types including Analysis , Backdoor , Benign , Brute Force , Bot, DoS , Fuzzers , Exploits , Generic , Infilteration , Shellcode ,Reconnaissance , Worms ,Theft , DDoS , Injection , Password , MITM , Ransomware , XSS and Scanning.