Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks-Reference-Cited by-同舟云学术

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Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks

Published:2023 Issue: Volume: Page:1-19
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Lederer Isabell¹,Mayer Rudolf¹^ORCID,Rauber Andreas¹

Affiliation:

1. SBA Research, Vienna, Austria

Funder

European Union’s Horizon 2020 research and innovation programme

BMK, BMAW, and the federal state of Vienna

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10143370.pdf?arnumber=10143370

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Detecting Adversarial Examples Using Surrogate Models;Machine Learning and Knowledge Extraction;2023-11-27

2. I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences;ACM Computing Surveys;2023-07-17

3. Federated Learning for Data Trading Portfolio Allocation With Autonomous Economic Agents;IEEE Transactions on Neural Networks and Learning Systems;2023

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