Privacy in Machine Learning
Sophisticated phishing tactics are increasingly leveraging machine learning, raising significant privacy concerns. Exploring privacy preserving machine learning, various techniques like differential privacy are discussed, emphasizing the balance between user protection and model accuracy. The conversation highlights the importance of innovative approaches, such as encrypted and federated learning, in addressing privacy threats while maintaining data integrity.In this clip
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Software Engineering Radio - the podcast for professional software developers
Episode 395: Katharine Jarmul on Security and Privacy in Machine Learning
Related Questions
What are the challenges in machine learning as discussed in the episode Differential Privacy Theory & Practice with Aaron Roth - #132 and the clip Differential Privacy Challenges?
What are the challenges in machine learning discussed in the episode Differential Privacy Theory & Practice with Aaron Roth - #132 and the clip Differential Privacy Challenges?