Large Scale Anonymous Collusion and its detection in crowdsourcing

Tao Han, Wentao Xu, Yili Fang, Xinyi Ding

Abstract: Highlights•We propose a novel large-scale anonymous collusion framework.•Our framework could fail conventional detection algorithms.•Our framework can help earn approximately 500% higher rewards.•We introduce a detection algorithm that works with varying sizes collusion groups.•Experiments show that using our method could ensure the quality of crowdsourced data.