SYN Flooding Attack Dataset (Syn_DDoS_2025)

This dataset contains 10,187,963 network traffic flow records with 88 features, representing both SYN flooding attack traffic and benign traffic. It has been curated to support research in intrusion detection systems (IDS), distributed denial-of-service (DDoS) attack detection, and machine learning–based network security. Each record provides detailed flow-level attributes, including: Source and destination ports, protocols, and flow duration Packet- and byte-level statistics TCP flag counts (SYN, ACK, FIN, RST, etc.) Derived statistical descriptors of network behavior The dataset is class-labeled with two categories: SYN attack: 7,131,574 records (~70%) Benign: 3,056,389 records (~30%) This imbalance mirrors real-world scenarios where attack traffic often dominates, making the dataset particularly valuable for evaluating resampling strategies, class balancing methods, and robust anomaly detection algorithms. The dataset is provided in CSV format for ease of use in data analysis and machine learning pipelines. A README.md file is included, containing a complete data dictionary describing all 88 features. This resource is intended to serve as a benchmark dataset for researchers, practitioners, and educators working in the fields of cybersecurity, computer networks, and artificial intelligence.