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 gives researchers the opportunity to develop IDS for RPL-based IoT networks using Artificial Intelligence and Machine Learning methods without simulating attacks. Simulating these attacks is an important step towards developing and testing protection mechanisms against such attacks by mimicking real-world attack scenarios. 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 important 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 an important step in the field of IoT security. By simulating four different routing attacks on IoT devices through cooja, you aim to predict the attacks by using the dataset created by these attacks in artificial intelligence and machine learning methods.