UAV-GCS Intrusion Detection Dataset (UAV-GCS-IDS)

The UAV-GCS-IDS dataset is designed for evaluating intrusion detection systems (IDS) in Unmanned Aerial Vehicle (UAV) communication environments. It captures network traffic between Ground Control Stations (GCS) and UAVs under both benign and malicious conditions. The dataset includes 10 multiclass labels, covering normal communication and 9 distinct cyberattack types such as DDoS, DoS, MITM, Scanning, Fake Landing, and Replay attacks. Each record is extracted from .pcap files using feature engineering and is structured in tabular format for use in machine learning-based IDS research.

UAV-GCS-IDS数据集旨在评估无人机（Unmanned Aerial Vehicle，UAV）通信环境中的入侵检测系统（intrusion detection systems，IDS）。该数据集捕获了地面控制站（Ground Control Stations，GCS）与无人机在正常与恶意两类场景下的网络流量。数据集包含10个多分类标签，涵盖正常通信场景与9种不同的网络攻击类型，例如分布式拒绝服务（DDoS）、拒绝服务（DoS）、中间人攻击（MITM）、扫描攻击、虚假着陆攻击与重放攻击等。每条记录均通过特征工程从.pcap格式文件中提取，并采用表格化结构构建，以供基于机器学习的入侵检测系统研究使用。