164 citations · 527 across the 37 of their papers we have counts for
4 papers · 1 filter
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
Micah Goldblum, Dimitris Tsipras, Chulin Xie +6
As machine learning systems grow in scale, so do their training data requirements, forcing practitioners to automate and outsource the curation of training data in order to achieve…
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Avi Schwarzschild, Micah Goldblum, Arjun Gupta +2
Data poisoning and backdoor attacks manipulate training data in order to cause models to fail during inference. A recent survey of industry practitioners found that data poisoning…
Headless Horseman: Adversarial Attacks on Transfer Learning Models
Ahmed Abdelkader, Michael J. Curry, Liam Fowl +5
Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks agai…
Adversarial Attacks on Machine Learning Systems for High-Frequency Trading
Micah Goldblum, Avi Schwarzschild, Ankit B. Patel +1
Algorithmic trading systems are often completely automated, and deep learning is increasingly receiving attention in this domain. Nonetheless, little is known about the robustness…