45 results
Search Results
2. Deep Neural Network Based Malicious Network Activity Detection Under Adversarial Machine Learning Attacks
3. Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness
4. Pixel Based Adversarial Attacks on Convolutional Neural Network Models
5. Performance Evaluation of Adversarial Attacks on Whole-Graph Embedding Models
6. Influence of Control Parameters and the Size of Biomedical Image Datasets on the Success of Adversarial Attacks
7. : Defending Against Adversarial Attacks Using Statistical Hypothesis Testing
8. Adversarial attacks on fingerprint liveness detection
9. On the robustness of vision transformers for in-flight monocular depth estimation
10. Adversarial attacks on graph-level embedding methods: a case study
11. Attack and Fault Injection in Self-driving Agents on the Carla Simulator – Experience Report
12. A Security-Oriented Architecture for Federated Learning in Cloud Environments
13. Risk Susceptibility of Brain Tumor Classification to Adversarial Attacks
14. Fruit-classification model resilience under adversarial attack
15. Reliable Aircraft Trajectory Prediction Using Autoencoder Secured with P2P Blockchain
16. Backdoor Mitigation in Deep Neural Networks via Strategic Retraining
17. Towards adversarial realism and robust learning for IoT intrusion detection and classification
18. Are Graph Neural Network Explainers Robust to Graph Noises?
19. Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations
20. Consistency Regularization Helps Mitigate Robust Overfitting in Adversarial Training
21. Addressing Adversarial Machine Learning Attacks in Smart Healthcare Perspectives
22. AGS: Attribution Guided Sharpening as a Defense Against Adversarial Attacks
23. Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review
24. Robustness Against Adversarial Attacks Using Dimensionality
25. BreakingBED: Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks
26. Robust Malware Detection System Against Adversarial Attacks
27. Targeting the Most Important Words Across the Entire Corpus in NLP Adversarial Attacks
28. A Lipschitz - Shapley Explainable Defense Methodology Against Adversarial Attacks
29. Analysis of Adversarial Attacks on Face Verification Systems
30. Enhancing Robustness of Graph Convolutional Networks via Dropping Graph Connections
31. Attacking Machine Learning Models for Social Good
32. Benchmarking Adversarial Attacks and Defenses for Time-Series Data
33. Overcoming Stealthy Adversarial Attacks on Power Grid Load Predictions Through Dynamic Data Repair
34. Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
35. Adversarial Attacks on Deep Learning Models of Computer Vision: A Survey
36. Robustification of Segmentation Models Against Adversarial Perturbations in Medical Imaging
37. Indirect Local Attacks for Context-Aware Semantic Segmentation Networks
38. Backdoor Attacks in Neural Networks – A Systematic Evaluation on Multiple Traffic Sign Datasets
39. Improving Robustness of Jet Tagging Algorithms with Adversarial Training
40. Fighting Adversarial Attacks on Online Abusive Language Moderation
41. Is Robustness the Cost of Accuracy? – A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
42. Ask, Acquire, and Attack: Data-Free UAP Generation Using Class Impressions
43. Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers
44. Robustifying Deep Networks for Medical Image Segmentation
45. Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness
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