Privacy, Verification, Robustness: A Cryptographer's perspective on ML
From Strachey Lectures by Oxford University
March 11, 2025 · 1h 4m
About this episode
The episode discusses how cryptographic tools can enhance trust in machine learning processes against adversarial threats.
Strachey Lecture: Privacy, Verification, Robustness: A Cryptographer's perspective on ML Cryptographic tools enable the safe use of technology platforms controlled by worst case computationally bounded adversaries.In this talk I will show how cryptographic paradigms and tools can be used to address trust issues in various phases of the machine learning pipeline. We will touch on approaches for achieving privacy, correctness, and robustness in presence of adversaries.
Topics covered
- cryptography
- machine learning
- privacy
- verification
- robustness
- adversarial attacks
Keywords
- cryptographic tools
- machine learning pipeline
- trust issues
- privacy
- correctness
- robustness
- adversaries
Mentioned in this episode
Organizations: Oxford University
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