Development of Embedded CAPTCHA Elements for Bot Prevention in Fischer Random Chess

Abstract

Cheating in chess can take many forms and has existed almost as long as the game itself. The advent of computers has introduced a new form of cheating into the game. Thanks to the computational power of modern-day computers, a player can use a program to calculate thousands of moves for him or her, and determine the best possible scenario for each move and countermove. These programs are often referred to as "bots," and can even play the game without any user interaction. In this paper, we describe a methodology aimed at preventing bots from participating in online chess games. The proposed approach is based on the integration of a CAPTCHA protocol into a game scenario, and the subsequent inability of bots to accurately track the game states. This is achieved by rotating the images of the individual chess pieces and adjusting their resolution in an attempt to render them unreadable by a bot. Feedback from users during testing shows that there is minimal impact on their ability to play the game. Players rated the difficulty of reading the pieces on a scale of one to ten, with an average rank of 6.5. However, the average number of moves to adjust to the distorted pieces was only 3.75. This tells us that, although it is difficult to read the pieces at first, it is easy to adjust quickly to the new image.

A survey and categorization of anomaly detection in online games

“…-Performing through the game log analysis of user behavior -Control a restriction time and scale -Bypass of detection by leak of detection rule -"User identification based on game-play activity patterns" [9] Network side [43][44][45] -Guarantee of game performance -Increasing computation power of encryption and decryption in traffic data -"Identifying MMORPG bots: A traffic analysis approach" [43] Client side [46][47][48] -Collecting of detection information in PC -Falling of game usability, and easy bypass of detection [7][8], [12][13], [18][19][20][21][22][23][24][25][26], [27][28][29], [32][33][34], [36][37], [42], [44][45][46] -High accuracy of anomaly detection -Limitation of application in real-time and client side because of using much time of data analysis -"Aimbot detection in online fps games using a heuristic method based on distribution comparison matrix" [23] Statistics [6], [9], [10], [14][15][16], [24], [30][31],…”