5G-NIDD: A Comprehensive Network Intrusion Detection Dataset Generated over 5G Wireless Network
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This work presents 5G-NIDD, a fully labeled dataset built on a functional 5G test network that can be used by those who develop and test AI/ML solutions. 5G-NIDD contains data extracted from a 5G testbed. The testbed is attached to 5G Test Network in University of Oulu, Finland. The data are extracted from tow base stations, each having an attacker node, several benign 5G users. The attacker nodes attack the server deployed in 5GTN MEC environment. The attack scenarios include DoS attacks and port scans. Under DoS attacks, the dataset contains ICMP Flood, UDP Flood, SYN Flood, HTTP Flood, and Slowrate DoS. Under port scans, the dataset contains SYN Scan, TCP Connect Scan, and UDP Scan. The dataset files are available in different formats. These files belong to a series of post-processing steps from network capture (pcapng) to encoded data (csv) ready to feed ML algorithms. Links to paper https://ieeexplore.ieee.org/document/11098458, https://arxiv.org/abs/2212.01298 If you use this dataset in your work, please cite the paper. Y. Siriwardhana et al., "Descriptor: 5G Wireless Network Intrusion Detection Dataset (5G-NIDD)," in IEEE Data Descriptions, doi: 10.1109/IEEEDATA.2025.3592888. @ARTICLE{11098458, author={Siriwardhana, Yushan and Samarakoon, Sehan and Porambage, Pawani and Liyanage, Madhusanka and Chang, Sang-Yoon and Kim, Jinoh and Kim, Jonghyun and Ylianttila, Mika}, journal={IEEE Data Descriptions}, title={Descriptor: 5G Wireless Network Intrusion Detection Dataset (5G-NIDD)}, year={2025}, volume={}, number={}, pages={1-12}, doi={10.1109/IEEEDATA.2025.3592888}}
本研究提出了5G-NIDD，这是一个基于功能性5G测试网络构建的全标注数据集，可供开发与测试人工智能/机器学习（AI/ML）解决方案的人员使用。 该数据集的数据源自一套5G测试床，该测试床接入芬兰奥卢大学的5G测试网络。 数据采集自两个基站，每个基站均配备一个攻击节点与若干正常5G用户终端。攻击节点针对部署在5GTN多接入边缘计算（Multi-Access Edge Computing, MEC）环境中的服务器发起攻击。 攻击场景涵盖拒绝服务（Denial of Service, DoS）攻击与端口扫描两类。其中拒绝服务攻击包含ICMP泛洪（ICMP Flood）、UDP泛洪（UDP Flood）、SYN泛洪（SYN Flood）、HTTP泛洪（HTTP Flood）以及慢速拒绝服务（Slowrate DoS）攻击；端口扫描场景则包含SYN扫描（SYN Scan）、TCP连接扫描（TCP Connect Scan）与UDP扫描（UDP Scan）。 该数据集提供多种格式的文件，覆盖从网络捕获文件（pcapng）到可直接输入机器学习算法的编码数据（CSV）的一系列后处理环节产物。 相关论文链接：https://ieeexplore.ieee.org/document/11098458、https://arxiv.org/abs/2212.01298 若在研究工作中使用该数据集，请引用以下论文： Y. Siriwardhana 等人，《数据集描述：5G无线网络入侵检测数据集（5G-NIDD）》，发表于《IEEE数据描述》（IEEE Data Descriptions），DOI: 10.1109/IEEEDATA.2025.3592888。 @ARTICLE{11098458, author={Siriwardhana, Yushan and Samarakoon, Sehan and Porambage, Pawani and Liyanage, Madhusanka and Chang, Sang-Yoon and Kim, Jinoh and Kim, Jonghyun and Ylianttila, Mika}, journal={IEEE Data Descriptions}, title={Descriptor: 5G Wireless Network Intrusion Detection Dataset (5G-NIDD)}, year={2025}, volume={}, number={}, pages={1-12}, doi={10.1109/IEEEDATA.2025.3592888}}
