Attack Detection
The necessity for strong security measures to fend off cyberattacks has increased due to the growing use of Industrial Internet of Things (IIoT) technologies. This research introduces IoTForge Pro, a comprehensive security testbed designed to generate a diverse and extensive intrusion dataset for IIoT environments. The testbed simulates various IIoT scenarios, incorporating network topologies and communication protocols to create realistic attack vectors and normal traffic patterns.
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The dataset, titled "SensorNetGuard: A Dataset for Identifying Malicious Sensor Nodes," comprises 10,000 samples with 21 features. It is designed to facilitate the identification of malicious sensor nodes in a network environment, specifically focusing on IoT-based sensor networks.
General Metrics
§ Node ID: The unique identifier for each node.
§ Timestamp: The time at which data or a packet is sent or received.
§ IP Address: Internet Protocol address of the node.
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Due to the large number of vulnerabilities in information systems and the continuous activity of attackers, techniques for malicious traffic detection are required to identify and protect against cyber-attacks. Therefore, it is important to intentionally operate a cyber environment to be invaded and compromised in order to allow security professionals to analyze the evolution of the various attacks and exploited vulnerabilities.
This dataset includes 2016, 2017 and 2018 cyber attacks in the HoneySELK environment.
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