To extend SOPHON to protect pre-trained models from fine-tuning in multiple restricted domains simultaneously, a few modifications and enhancements can be implemented. One approach is to introduce a multi-task learning framework where the model is trained to resist fine-tuning in multiple restricted domains concurrently. This can involve incorporating different loss functions for each domain and optimizing the model parameters to perform poorly in all specified domains. Additionally, the fine-tuning simulation process can be expanded to simulate various fine-tuning strategies across different domains, ensuring that the model remains non-fine-tunable in each domain. By adjusting the optimization process to handle multiple restricted domains, SOPHON can effectively protect pre-trained models from being fine-tuned for unethical or harmful tasks across various domains simultaneously.