State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey

arXiv:2404.16847v1 Announce Type: new
Abstract: This paper examines the evolving landscape of machine learning (ML) and its profound impact across various sectors, with a special focus on the emerging field of Privacy-preserving Machine Learning (PPML). As ML applications become increasingly integral to industries like telecommunications, financial technology, and surveillance, they raise significant privacy concerns, necessitating the development of PPML strategies. The paper highlights the unique challenges in safeguarding privacy within ML frameworks, which stem from the diverse capabilities of potential …

applications art arxiv cs.ai cs.cr datasets emerging financial financial technology focus impact industries machine machine learning preservation privacy sectors special state survey technology telecommunications