Transferable Adversarial Attack based on Integrated Gradients
Authors: Yi Huang, Adams Wai-Kin Kong
ICLR 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results demonstrate that TAIG outperforms the state-of-the-art methods. |
| Researcher Affiliation | Academia | Yi Huang, Adams Wai-Kin Kong School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue, Singapore 639798 {yi.huangy,adamskong}@ntu.edu.sg |
| Pseudocode | No | The paper describes the algorithm using equations and narrative, but does not include a formally structured pseudocode block or an 'Algorithm' label. |
| Open Source Code | Yes | The code will available at https://github.com/yihuang2016/TAIG. |
| Open Datasets | Yes | The experiments are conducted on Image Net (Russakovsky et al., 2015) validation set. |
| Dataset Splits | No | The paper uses pre-trained models and the ImageNet validation set as source data for generating and evaluating adversarial examples, but it does not specify train/validation/test splits for its own experimental setup or attack algorithm training. |
| Hardware Specification | Yes | All the experiments are performed on two NVIDIA Ge Force RTX 3090 with the main code implemented using Py Torch. |
| Software Dependencies | No | The paper mentions 'Py Torch' but does not specify a version number or other software dependencies with specific versions. |
| Experiment Setup | Yes | Res Net50 (He et al., 2016) is selected as a surrogate model to generate adversarial examples to compare with the state-of-the-art methods. ... By following Lin BP, the maximum allowable perturbations are set as ε = 0.03, 0.05, 0.1. ... Thirty sampling points are used to estimate TAIG-S. For TAIG-R, the number of turning point E is set to 30 and τ is set equal to ε. ... for Lin BP, we keep the default setting where the number of iterations is 300 and the step size is 1/255 for all different ε. ... TAIG-S and TAIG-R are run 20, 50, and 100 iterations with the same step size as Lin BP for ε = 0.03, 0.05, 0.1, respectively. |