mlsanityData to 7 Oct 2026

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

arXiv 1709.04114 ↗First posted 13 Sep 2017stat.ML cs.CR cs.LGcited by 154

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Abstract (arXiv)

Recent studies have highlighted the vulnerability of deep neural networks (DNNs) to adversarial examples - a visually indistinguishable adversarial image can easily be crafted to cause a well-trained model to misclassify. Existing methods for crafting adversarial examples are based on L2 and L_∞ distortion metrics. However, despite the fact that L1 distortion accounts for the total variation and encourages sparsity in the perturbation, little has been developed for crafting L1-based adversarial examples. In this paper, we formulate the process of attacking DNNs via adversarial examples as an elastic-net regularized optimization problem. Our elastic-net attacks to DNNs (EAD) feature L1-oriented adversarial examples and include the state-of-the-art L2 attack as a special case. Experimental results on MNIST, CIFAR10 and ImageNet show that EAD can yield a distinct set of adversarial examples with small L1 distortion and attains similar attack performance to the state-of-the-art methods in different attack scenarios. More importantly, EAD leads to improved attack transferability and complements adversarial training for DNNs, suggesting novel insights on leveraging L1 distortion in adversarial machine learning and security implications of DNNs.

Key facts. Cited by 154 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Sep 2017.

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Citing papers per year: 2021: 55; 2022: 43; 2023: 22; 2024: 19; 2025: 10; 2026: 5.

154 papers.

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  1. 2021When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?cited by 76
  2. 2022Frequency-driven Imperceptible Adversarial Attack on Semantic Similaritycited by 76
  3. 2021Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blinkcited by 75
  4. 2023A Pilot Study of Query-Free Adversarial Attack against Stable Diffusioncited by 75
  5. 2021On Improving Adversarial Transferability of Vision Transformerscited by 70
  6. 2021AdvDrop: Adversarial Attack to DNNs by Dropping Informationcited by 55
  7. 2021Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraintscited by 50
  8. 2021Mind the box: l1-APGD for sparse adversarial attacks on image classifierscited by 50
  9. 2022NICGSlowDown: Evaluating the Efficiency Robustness of Neural Image Caption Generation Modelscited by 47
  10. 2021Partition-based formulations for mixed-integer optimization of trained ReLU neural networkscited by 39
  11. 2021Improved, Deterministic Smoothing for L_1 Certified Robustnesscited by 39
  12. 2021TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothnesscited by 37
38 more
  1. 2021Consistent Counterfactuals for Deep Modelscited by 37
  2. 2021Deep Learning-Based Autonomous Driving Systems: A Survey of Attacks and Defensescited by 29
  3. 2021A Review of Adversarial Attack and Defense for Classification Methodscited by 29
  4. 2022An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applicationscited by 29
  5. 2021Machine learning pipeline for battery state of health estimationcited by 28
  6. 2022Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbationscited by 26
  7. 2021Adversarial Robustness against Multiple and Single lp-Threat Models via Quick Fine-Tuning of Robust Classifierscited by 23
  8. 2023A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attackscited by 19
  9. 2021Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselinescited by 17
  10. 2021Mutual Adversarial Training: Learning together is better than going alonecited by 17
  11. 2022Reverse Engineering of Imperceptible Adversarial Image Perturbationscited by 17
  12. 2021Security and Privacy for Artificial Intelligence: Opportunities and Challengescited by 16
  13. 2021Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attackscited by 16
  14. 2021SoK: Anti-Facial Recognition Technologycited by 16
  15. 2021Attack as Defense: Characterizing Adversarial Examples using Robustnesscited by 14
  16. 2022Are AlphaZero-like Agents Robust to Adversarial Perturbations?cited by 14
  17. 2024AttackBench: Evaluating Gradient-based Attacks for Adversarial Examplescited by 14
  18. 2022Towards Lightweight Black-Box Attacks against Deep Neural Networkscited by 13
  19. 2023Towards Reliable Evaluation and Fast Training of Robust Semantic Segmentation Modelscited by 12
  20. 2021TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attackcited by 11
  21. 2021Deep Reinforcement Learning Policies Learn Shared Adversarial Features Across MDPscited by 11
  22. 2022Holistic Adversarial Robustness of Deep Learning Modelscited by 11
  23. 2022Adversarial Laser Spot: Robust and Covert Physical-World Attack to DNNscited by 11
  24. 2022Adversarial Color Film: Effective Physical-World Attack to DNNscited by 11
  25. 2021Statistical Perspectives on Reliability of Artificial Intelligence Systemscited by 10
  26. 2022What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradictioncited by 10
  27. 2024Verification of Neural Networks' Global Robustnesscited by 10
  28. 2021On the robustness of randomized classifiers to adversarial examplescited by 9
  29. 2024Prompt-Driven Contrastive Learning for Transferable Adversarial Attackscited by 9
  30. 2025When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Modelscited by 9
  31. 2021PDPGD: Primal-Dual Proximal Gradient Descent Adversarial Attackcited by 8
  32. 2021Adversarial Attack and Defense in Deep Rankingcited by 8
  33. 2021Discriminator-Free Generative Adversarial Attackcited by 8
  34. 2021ε-weakened Robustness of Deep Neural Networkscited by 8
  35. 2022Machine Learning in NextG Networks via Generative Adversarial Networkscited by 8
  36. 2022A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunitiescited by 8
  37. 2021Perceptually Constrained Adversarial Attackscited by 7
  38. 2024σ-zero: Gradient-based Optimization of ℓ0-norm Adversarial Examplescited by 7

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