| _ | steal | _ |
|---|---|---|
| Can't | steal | ? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders |
| Can't | steal | ? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders |
| Copycat CNN: Are random non-Labeled data enough to | steal | knowledge from black-box models? |
| _ | stealing | _ |
|---|---|---|
| Black-Box Dissector: Towards Erasing-Based Hard-Label Model | stealing | Attack |
| Can't Steal? Cont-Steal! Contrastive | stealing | Attacks Against Image Encoders |
| Defending Against Model | stealing | Attacks With Adaptive Misinformation |
| Knockoff Nets: | stealing | Functionality of Black-Box Models |
| MAZE: Data-Free Model | stealing | Attack Using Zeroth-Order Gradient Estimation |
| Prediction Method of Anti-Electricity | stealing | Based on Big Data of Electric Power, A |
| Study on Image Color | stealing | in Log-Polar Space |
| Towards Data-Free Model | stealing | in a Hard Label Setting |
| _ | stealth | _ |
|---|---|---|
| Environmental Sensitivity of Large | stealth | Longwave Antenna Systems |
| Moving-Target Tracking by Cognitive RF | stealth | Radar Using Frequency Diverse Array Antenna |
| stealth | Navigation: Planning and Behaviors | |
| stealth | Terrain Navigation | |
| stealth | Terrain Navigation for Multi-Vehicle Path Planning | |
| stealth | Terrain Navigation with Bounding Overwatch | |
| stealth | vision for protecting privacy |
| _ | stealthy | _ |
|---|---|---|
| Adversarial Sticker: A | stealthy | Attack Method in the Physical World |
| BppAttack: | stealthy | and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning |
| Improving Robustness Against | stealthy | Weight Bit-Flip Attacks by Output Code Matching |
| Pasadena: Perceptually Aware and | stealthy | Adversarial Denoise Attack |
| Resilient Distributed Kalman Filtering Under Bidirectional | stealthy | Attack, A |
| RFLA: A | stealthy | Reflected Light Adversarial Attack in the Physical World |
| Risk Assessment for Connected Vehicles Under | stealthy | Attacks on Vehicle-to-Vehicle Networks |
| Semantically | stealthy | Adversarial Attacks against Segmentation Models |
| Shadows can be Dangerous: | stealthy | and Effective Physical-world Adversarial Attack by Natural Phenomenon |
| Simtrojan: | stealthy | Backdoor Attack |
| stealthy | Backdoor Attack Against Speaker Recognition Using Phase-Injection Hidden Trigger | |
| stealthy | Frequency-Domain Backdoor Attacks: Fourier Decomposition and Fundamental Frequency Injection | |
| stealthy | Physical Masked Face Recognition Attack via Adversarial Style Optimization |