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数据集专为评估无人机（Unmanned Aerial Vehicle，UAV）通信环境下的入侵检测系统（Intrusion Detection System，IDS）而设计。该数据集捕获了地面控制站（Ground Control Station，GCS）与无人机在正常及恶意场景下的网络流量。数据集包含10个多分类标签，涵盖正常通信以及9种不同的网络攻击类型，例如分布式拒绝服务（Distributed Denial of Service，DDoS）、拒绝服务（Denial of Service，DoS）、中间人攻击（Man-in-the-Middle Attack，MITM）、扫描攻击、虚假着陆攻击与重放攻击。每条记录均通过特征工程从.pcap文件中提取，并采用表格格式构建，可用于基于机器学习的入侵检测系统相关研究。