DeepSec 2024 Talk: Cheating Detection in Chess using Neural Network – Zura Kevanishvili
During the talk, I will address the escalating issue of cheating in online chess, underscored by recent incidents like Hans Niemann’s case, highlighting the urgent need for effective solutions to maintain fair play and uphold competitive integrity. I will present our innovative approach to detecting AI assistance in chess, using advanced neural networks. Our research involves a comprehensive analysis of extensive chess game data, encompassing moves from established engines like Stockfish to innovative neural networks such as Maia, Maia individual and its components. Key aspects of our methodology include: Centipawn Deviations: Evaluating deviations from typical computer strategies to identify moves influenced by AI. Human-like Play Recognition: Utilizing Maia’s and Maia Individual’s capability to discern human-specific playing styles, enhancing our ability to distinguish genuine human play from computer-assisted moves. Move Time Distribution: Analyzing patterns in