2021 ICCV Admix: Enhancing the Transferability of Adversarial Attacks 2021 arxiv Direction-Aggregated Attack for Transferable Adversarial Examples 每次迭代时,执行N次对图片随机加入高斯噪声的操作,把这N次的梯度方向相加,作为最终的梯度更新方向 梯度生成: 2018 CVPR Boosting Adversarial Attacks with Momentum 2020...
The cross-model transfer characteristics of adversarial examples limit the application of DNNs in real life, and the threat of adversarial examples to DNNs has stimulated researchers' interest in adversarial attacks. Recently, researchers have proposed several adversarial attack m...
Chain of Attack: On the Robustness of Vision-Language Models AgainstTransfer-Based Adversarial AttacksPeng Xie * , Yequan Bie * , Jianda Mao, Yangqiu Song, Yang Wang, Hao Chen B , Kani Chen BThe Hong Kong University of Science and Technology{pxieaf, ybie}@connect.ust.hkAbstractPre-traine...
2.3 Black-box attacks based on both transferability and queries 这里仍然有一些方法结合了对抗样本的可移植性和模型查询来进行黑盒攻击。 对抗样本论文学习(3):Practical Black-Box Attacks against Machine Learning Papernot等 通过用合成的数据集训练一个局部替代模型来模拟黑箱模型,其中数据集的标签由黑箱模型通过...
23 proposed an auto-encoder-based TL approach to detect the network attacks in IoT. Later, Singla et al.27 used adversarial domain adaptation to develop the TL model to use the knowledge attained from one NID dataset for another domain/network with the less labeled dataset. The existing ...
“Responsible Consumption and Production” sustainable development goals. In addition to already available methods for early disease detection and classification facing overfitting and fine feature extraction complexities during the training process, how early signs of green attacks can be identified or ...
Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer" - thunlp/StyleAttack
Deep learning-based high-precision computerized brain tumor diagnosis helps to obtain significant clinical features for proper treatment. Research also revealed that medical deep learning systems are easily compromised by several small imperceptible perturbation strategies and resultant adversarial attacks. Medica...
Adversarial attacks provide a good way to study the robustness of deep learning models. One category of methods in transfer-based black-box attack utilizes several image transformation operations to improve the transferability of adversarial examples, which is effective, but fails to take the specific...
However, existing transfer-based adversarial attacks usually have high attack success rates (ASR) on white-box models, but relatively low ASR on black-box models. In addition, most of the existing transfer attacks actually perturb full pixels, resulting in a perturbation added to the redundant ...