Privacy Preserving Deep Learning

Privacy-preserving deep learning aims to train models while ensuring the privacy and security of the training dataset. Its core objective is to prevent the leakage of sensitive information during the model training process by adopting techniques such as differential privacy, thereby safeguarding the privacy rights of data subjects. In the field of natural language processing, the application of this technology can effectively enhance data utilization efficiency while meeting stringent privacy compliance requirements, making it highly valuable.