In the era of the rapid development of IoT, artificial intelligence and big data, Information security issues are on the rise and the importance of cyber security has gradually gained attention. Many studies using game-based learning to teach the cyber security concept and literacy have gained good results. For example, "iMonsters" card game, developed by KDELab of Asia University, currently has been effective in the teaching and has a lot of favorite players. But according to the feedback from the players, there still exist some problems. In this study, we will solve these problems to achieve a better balance between the gameplay, domain knowledge and education. We first proposed the game refining algorithm using Sequential Pattern Mining to strengthen the iMonsters game rules. For example, some anomalies have been found including the existence of the barrier of the game and the different interpretations of the game rules. Therefore, the game rule refining algorithm can help us to refine the game rules.
We then conducted the teaching and testing of the card game through the winter camp of the Asian University. According to the results of pre-tests, post-tests and questionnaires, we further modified the rules of the game and obtained the players' learning status. In addition, we applied the Internet security knowledge building algorithm proposed by the KDELab to analyze the collected real Internet security incidents and to modify the iMonsters card game rules if the new incidents cannot be solved. Finally the game rules evolution algorithm was proposed to modify the game rules to conform to the ever-changing cyber-attack techniques.