The Graph-Based Dataset for IoT Network Attack Detection is a curated collection of data specifically designed for research and development in the field of cybersecurity, focusing on the detection of attacks in Internet of Things (IoT) networks. This graph-based dataset provides researchers, developers, and practitioners with a comprehensive resource to evaluate and benchmark various detection algorithms and systems in real-world IoT network environments.
## Key Features
- Graph Representation: Network traffic data represented as graphs, facilitating intuitive visualization and analysis.
- Attack Scenarios: Diverse attack scenarios, including DDoS attacks, HTTP Get/Post flood, TCP SYN flood, UDP flood, ICMP flood, brute force and port scanning.
- Anomaly Labels: Ground truth labels for anomalous network activity, enabling supervised learning approaches for attack detection.
## Dataset Description
The dataset consists of network traffic data captured from emulated IoT network environments, where various attack scenarios have been emulated. The network traffic data is represented in the form of graphs, capturing the interactions and relationships between different devices, services, and communication patterns within the IoT network. Each graph in the dataset represents a snapshot of network activity over a specific time period, enabling analysis of attack patterns and behaviors. The following figure presents the general netwok architecture.
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## 3. Data capture
To capture the network trafic in our environment, we used Wireshark tool to record the network data in pcap format and used a flow capture tool called CICFlowmeter.
### Packet
we use the Wireshark tool to record the network data in pcap format. They are available in the GRASEC-IoT gitlab \cite{grasec}. An exemple of features:
- Graph Representation: Network traffic data represented as graphs, facilitating intuitive visualization and analysis.
- Attack Scenarios: Diverse attack scenarios, including DDoS attacks, HTTP Get/Post flood, TCP SYN flood, UDP flood, ICMP flood, brute force and port scanning.
