Game bot detection in online role player game through behavioural features

The market of online games is highly increasing in the last years and thanks to the availability of always more effective gaming infrastructures and the increased quality of the developed games. The diffusion of on line games also increases the use of game bots to automatically perform malicious tasks obtaining some rewards (with a consequent economical advantage or popularity) in the game community with low effort. These causes the disappointment of the game players community becoming a critical issue for the game developers. For this reason, distinguishing between game bots and human behaviour being became essential in order to detect the malicious tasks and consequently increase the players satisfaction. In this paper authors propose an approach to the game bot detection in the online role player games based on the adoption of machine learning techniques in order to discriminate between users and game bots basing on some user behavioral features. The approach is applied to a real-world dataset of a popular role player game and the obtained results are encouraging.