Cyber Security Training with Generative Artificial Intelligence Supported Web Platform Using IoT Cyber Threat Scenarios

Nowadays, IoT devices have a remarkable place in daily life activities. Because of their wide application scope, cyber-attacks have started to increase as causing a critical issue in terms of data security. Because of this, some analyses within IoT network environments should be done for prevention and detection purposes. At this point, it is also important to train users to establish an awareness about cyber threats for IoT and how to analyze network environments in case of unexpected situations. This paper introduces a Web platform, which provides some IoT security scenarios to learn about how to understand / detect cyber threats and test their knowledge. In detail, the platform uses a synthetic dataset of network data pointing malicious or benign network activities. The dataset was generated by Generative Adversarial Networks, which was fed by some original network traffic datasets. Thanks to the synthetic dataset, the platform is able to provide tests or scenarios for randomly chosen network traffic data so that users can learn and test their skills in terms of IoT security. The applications revealed that GAN was successful enough to generate synthetic traffic datasets and the users were positive about their experiences with the developed Web platform.