Adversarial Examples: Attacks and Defenses for Deep Learning
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- Type
- preprint
- Published
- 2017-12-19
- Cited by
- 1,852
- References
- 173
- Access
- Open access
- OpenAlex
- https://openalex.org/W2777449390
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:21569987
Keywords
Adversarial system, Deep learning, Deep neural networks, Computer science, Artificial intelligence
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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- Intriguing properties of neural networks
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- Analysis of classifiers’ robustness to adversarial perturbations
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Robots that can adapt like animals
- Distilling the Knowledge in a Neural Network
- The IBM 2015 English conversational telephone speech recognition system
- Towards Deep Neural Network Architectures Robust to Adversarial Examples
- Deep neural network based malware detection using two dimensional binary program features
- Fully convolutional networks for semantic segmentation
- Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
- Large-scale malware classification using random projections and neural networks
- Systematic Poisoning Attacks on and Defenses for Machine Learning in Healthcare
- Multiple classifier systems for robust classifier design in adversarial environments
- Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
- Going deeper with convolutions
- Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization
- Droid-Sec
Cited by
- Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk
- Deep packet: a novel approach for encrypted traffic classification using deep learning
- One Pixel Attack for Fooling Deep Neural Networks
- Adversarial frontier stitching for remote neural network watermarking
- How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models
- Learning Fast and Slow: Propedeutica for Real-Time Malware Detection
- Security and Privacy Approaches in Mixed Reality
- Adversarial Vulnerability of Neural Networks Increases With Input Dimension
- Adversarial Examples on Discrete Sequences for Beating Whole-Binary Malware Detection
- Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch
- Fibres of Failure: Classifying errors in predictive processes
- Indoor Scene Understanding in 2.5/3D: A Survey
- Defending against Adversarial Images using Basis Functions Transformations
- Low Resource Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers
- Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
- A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends
- Training verified learners with learned verifiers
- Bidirectional Learning for Robust Neural Networks
- Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
- Non-Negative Networks Against Adversarial Attacks
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