The development of artificial intelligence has significantly transformed people's lives. However, it has also posed a significant threat to privacy and security, with numerous instances of personal information being exposed online and reports of criminal attacks and theft. Consequently, the need to achieve intelligent protection of personal information through machine learning algorithms has become a paramount concern. Artificial intelligence leverages advanced algorithms and technologies to effectively encrypt and anonymize personal data, enabling valuable data analysis and utilization while safeguarding privacy. This paper focuses on personal data privacy protection and the promotion of anonymity as its core research objectives. It achieves personal data privacy protection and detection through the use of machine learning's differential privacy protection algorithm. The paper also addresses existing challenges in machine learning related to privacy and personal data protection, offers improvement suggestions, and analyzes factors impacting datasets to enable timely personal data privacy detection and protection.

翻译：人工智能的发展极大地改变了人们的生活，但也对隐私和安全构成了重大威胁，个人信息在线泄露以及犯罪攻击和盗窃事件屡见不鲜。因此，通过机器学习算法实现个人信息的智能保护已成为首要关注的问题。人工智能利用先进的算法和技术，能够有效地对个人数据进行加密和匿名化处理，在保护隐私的同时实现有价值的数据分析和利用。本文以个人数据隐私保护和促进匿名化作为核心研究目标，通过使用机器学习的差分隐私保护算法来实现个人数据隐私的保护和检测。论文还探讨了机器学习中与隐私和个人数据保护相关的现有挑战，提出了改进建议，并分析了影响数据集的因素，以实现对个人数据隐私的及时检测和保护。