Poisoning Web-Scale Training Datasets is Practical-Reference-Cited by-同舟云学术

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Poisoning Web-Scale Training Datasets is Practical

Published:2024-05-19 Issue: Volume:29 Page:407-425
ISSN:
Container-title:2024 IEEE Symposium on Security and Privacy (SP)
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Author:

Carlini Nicholas¹,Jagielski Matthew¹,Choquette-Choo Christopher A.¹,Paleka Daniel²,Pearce Will³,Anderson Hyrum⁴,Terzis Andreas¹,Thomas Kurt⁵,Tramèr Florian²

Affiliation:

1. Google DeepMind

2. ETH,Zurich

3. NVIDIA

4. Robust Intelligence

5. Google

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10646615/10646598/10646610.pdf?arnumber=10646610

Reference116 articles.

1. Venomave: Targeted Poisoning Against Speech Recognition

2. Contour: A practical system for binary transparency;Al-Bassam,2018

3. Poisoning deep reinforcement learning agents with in-distribution triggers;Ashcraft,2021

4. Wikipedia:Database download;Authors

5. The Do’s and Don’ts for CNN-Based Face Verification

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. Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally;IEEE Transactions on Artificial Intelligence;2024-09

2. FCert: Certifiably Robust Few-Shot Classification in the Era of Foundation Models;2024 IEEE Symposium on Security and Privacy (SP);2024-05-19

3. Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models;2024 IEEE Symposium on Security and Privacy (SP);2024-05-19

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