Traffic Analysis: IoT and anomalies dataset.

This dataset, generated as part of the SecBluRed project (funded by the European Union - NextGenerationEU and CDTI, expediente EXP 00152981 / MIG-20221051 ), consists of PCAP (Packet Capture) files. These files contain network traffic from a controlled laboratory environment designed to simulate Industrial IoT (IIoT) communications using the MQTT protocol. The traffic scenarios include benign (normal) device operations, a variety of cyberattacks, and different forms of communication noise. This dataset is intended to support research and development in network security, particularly for intrusion detection and anomaly detection within IoT and IIoT ecosystems. The cyberattacks captured include Code Injection, Brute Force, Node Spoofing, Denial of Service (DoS/DDoS), Data Poisoning, Network Contamination, and Wormhole attacks. The dataset also features instances of network noise, such as Synchronization Problems, interference from Physical Obstructions, and Environmental Noise reflecting climatic factors. Notably, a subset of these PCAP files, particularly those relevant for detecting attacks that manipulate network association or authentication processes (e.g., certain Wormhole attack variants ), were captured in "monitor mode." This was necessary to capture 802.11 management frames, including EAPOL (Extensible Authentication Protocol over LAN) packets. These frames are critical for the analysis and detection of threats that exploit Wi-Fi connection and authentication mechanisms. Potential Applications: Development and benchmarking of Intrusion Detection Systems (IDS) and Machine Learning models. Analysis of network traffic behavior and anomaly patterns in IoT networks. In-depth study of diverse attack vectors and noise manifestations targeting IoT infrastructures. Research into traffic classification techniques for distinguishing between normal traffic, cyberattacks, and noise in IoT communications. This dataset aims to provide a realistic and varied collection of network captures to foster advancements in cybersecurity and network analysis for Industrial IoT systems. This work has been realised by the MTP Research and Development Department (www.mtp.es) within the scope of the SecBluRed project.