Emotional Analysis of Learning Cybersecurity with Games

The constant growth of cyber-attacks poses an increase for more qualified people with cybersecurity knowledge. The cybersecurity professionals are high demanding to have adequate motivation and reasonable skills to detect, prevent, respond and mitigate the effects of such threats. Cyber Security Games have emerged as a well-fitted technology to engage users in learning processes. In this work, we analyze the emotional parameters of people while learning cybersecurity through computer games. The data are gathered using a non-invasive Brain-Computer Interface (BCI), a neurotechnological discoveries based on Electroencephalography (EEG) which enabled to study the signals directly from the users’ brains. We analyze six performance metrics (engagement, focus, excitement, stress, relaxation, and interest) of 12 users while playing computer games to measure the effectiveness of the games to attract the attention of the participants having previous knowledge. The collected data from the brain signal through the Emotiv EPOC+ neuroheadset were extracted and imported into a powerful stream data database InfluxDB and employed Grafana tool for visualizing the data to show the performance parameters with a timestamp for easy analysis. Two games “Buffer Overflow” and “Access Control” were used for the analysis. The analysis of these factors were mainly conducted from the game point of view and not from the real feelings of the participant. The results show participants were more engaged with parts of the games that teach “Access Control” than others that teach “Buffer Overflow” mainly due to the interactivity of the game. We also discuss the future of BCI in the creation of effective games to teach cybersecurity topics