Defending against Machine Learning based Inference Attacks via
Adversarial Examples: Opportunities and Challenges

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Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges

17 September 2019

Neil Zhenqiang Gong

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Papers citing "Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges"

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Title
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 135 3 0 20 Nov 2023
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks Kendra Albert Maggie K. Delano B. Kulynych Ramnath Kumar AAML 120 5 0 11 Jul 2021
Federated Learning With Highly Imbalanced Audio Data Marc C. Green Mark D. Plumbley FedML 59 4 0 18 May 2021
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models A. Salem Yannick Sautter Michael Backes Mathias Humbert Yang Zhang AAML SILM AI4CE 59 40 0 06 Oct 2020
Face-Off: Adversarial Face Obfuscation Varun Chandrasekaran Chuhan Gao Brian Tang Kassem Fawaz S. Jha Suman Banerjee PICV 81 44 0 19 Mar 2020
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 98 397 0 23 Sep 2019