Stealing Knowledge from Protected Deep Neural Networks Using Composite Unlabeled Data

9 December 2019

Papers citing "Stealing Knowledge from Protected Deep Neural Networks Using Composite Unlabeled Data"

5 / 5 papers shown

Title
Towards Few-Call Model Stealing via Active Self-Paced Knowledge Distillation and Diffusion-Based Image Generation Vlad Hondru Radu Tudor Ionescu DiffM 97 2 0 29 Sep 2023
Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks Isabell Lederer Rudolf Mayer Andreas Rauber 98 19 0 22 Apr 2023
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences Daryna Oliynyk Rudolf Mayer Andreas Rauber 114 114 0 16 Jun 2022
Copycat CNN: Are Random Non-Labeled Data Enough to Steal Knowledge from Black-box Models? Jacson Rodrigues Correia-Silva Rodrigo Berriel C. Badue Alberto F. de Souza Thiago Oliveira-Santos MLAU 61 15 0 21 Jan 2021
DeepMimic: Mentor-Student Unlabeled Data Based Training Itay Mosafi E. David N. Netanyahu 59 6 0 24 Nov 2019