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• Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
  2016 · 1420 citations
• On the (Statistical) Detection of Adversarial Examples
  2017 · 377 citations
• Adversarial Perturbations Against Deep Neural Networks for Malware Classification
  2016 · 321 citations
• Towards the Science of Security and Privacy in Machine Learning
  2016 · 192 citations
• Practical Black-Box Attacks against Machine Learning
  2016 · 101 citations
• The Limitations of Deep Learning in Adversarial Settings
  2015 · 72 citations
• On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping
  2020 · 70 citations
• On the Effectiveness of Defensive Distillation
  2016 · 58 citations
• A Marauder's Map of Security and Privacy in Machine Learning
  2018 · 11 citations
• Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
  2015 · 8 citations
• Increasing the Cost of Model Extraction with Calibrated Proof of Work
  2022 · 7 citations
• Adversarial Examples in Constrained Domains
  2020 · 4 citations
• SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems
  2020 · 3 citations
• AI Agents Enable Adaptive Computer Worms
  2026 · 2 citations
• Neighbors From Hell: Voltage Attacks Against Deep Learning Accelerators on Multi-Tenant FPGAs
  2020 · 2 citations