In tis paper we propose a methodology to anonymize individual mobility trajectories. The goal is to be able to protect data against the reidentification risk. The proposed solution is based on a coclustering method. The coclustering is used to build an aggregated representation of the data, then a Markov mobility model is designed for each cluster of trajectories. The mobility model is then used to draw synthetic individual trajectories. We show that these synthetic data preserve sufficient information to be used in place of the real data. Finally the protection against the reidentification risk is evaluated.