Stanford Seminar - Persistent and Unforgeable Watermarks for Deep Neural Networks

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Overview

Stanford Seminar - Persistent and Unforgeable Watermarks for Deep Neural Networks

Explore a Stanford seminar on persistent and unforgeable watermarks for deep neural networks. Delve into the increasing popularity of DNNs, their training challenges, and the importance of IP protection for model owners.

Learn about various watermarking techniques, including embedding through regularizers, backdoors, and cryptographic commitments. Discover two new training techniques: out-of-bound values and null embedding. Examine the concept of wonder filters and their role in watermark design.

Understand the process of watermark generation, injection, and verification. Evaluate the effectiveness of these techniques based on low distortion, reliability, absence of false positives, authentication capabilities, piracy resistance, and persistence.

Gain insights into the future of DNN watermarking and its implications for intellectual property protection in the field of artificial intelligence.

University: Stanford University

Provider: YouTube

Categories: Deep Learning Courses, Cryptography Courses

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