ROUT-4-2023: RPL Based Routing Attack Dataset for IoT

This dataset consists of “.csv” files of 4 different routing attacks (Blackhole Attack, Flooding Attack, DODAG Version Number Attack, and Decreased Rank Attack) targeting the RPL protocol, and these files are taken from Cooja (Contiki network simulator). It allows researchers to develop IDS for RPL-based IoT networks using Artificial Intelligence and Machine Learning methods without simulating attacks. Simulating these attacks by mimicking real-world attack scenarios is essential to developing and testing protection mechanisms against such attacks. For these researchers, it may offer an alternative approach to intrusion detection systems that have limitations of traditional methods. This requires identifying appropriate attributes that include characteristics of attacks, analyzing network traffic data, and considering other relevant parameters. It is also essential that your dataset is balanced and representative so that your model can accurately identify and predict different types of attacks. In conclusion, this study is a critical step for IoT security. By simulating four routing attacks to IoT devices through Cooja, we present a new dataset to detect attacks for applications in artificial intelligence and machine learning methods.