Universal Adversarial Perturbations (UAP) 很“便宜” - 单个噪声可用于导致模型错误标记大量图像。(与基于每个图像生成扰动的通常攻击不同。但这些更有效)。论文还发现 UAP 可以跨不同模型,因此它们也可以用于黑盒攻击设置,因此研究它们很重要。 UAP vs Adversarial Perturbation:为了攻击给定的模型,在一个常见的对抗...
In addition, we also demonstrate how universal adversarial training benefits the robustness of the model against universal attacks. We release our tool GUAP on https://github.com/TrustAI/GUAP.doi:10.1007/s10994-023-06306-zYanghao ZhangWenjie Ruan...
Clean Image + Perturbation == Adversarial Image Here is the output of a UAN throughout training: Data set-up For ImageNet Follow instructionshttps://github.com/amd/OpenCL-caffe/wiki/Instructions-to-create-ImageNet-2012-data. The validation set should be in path./imagenet/data/val/. There ...
The script "Universal_perturbations_multi.py" contains the implementation of the algorithm used for the generation of universal adversarial perturbations. The program takes as input the following parameters: model_path: path to the target model. We assume that the model is a frozen TF classifier (...
Universal and Transferable Adversarial Attacks on Aligned Language Models 新元 dirtycomputer.github.io2 人赞同了该文章 代码: https://github.com/llm-attacks/llm-attacksgithub.com/llm-attacks/llm-attacks 论文: https://arxiv.org/abs/2307.15043arxiv.org/abs/2307.15043 如上图:左边是带有危险...
本文发表在AAAI2023,有完整代码,据github的项目所说还是Oral,即上台做pre的,应该是一篇好论文。一作来自厦门大学。 Abstract The ensemble attack with average weights can be leveraged for increasing the transferability of universal adversarial perturbation (UAP) by training with multiple Convolutional Neural Netw...
《Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models》(2023) GitHub: github.com/nmndeep/revisiting-at《Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?》(2023) GitHub: github.com/SamsungSAILMontreal/ghn3...
Therefore, it produces more successful attacks when the number of training samples is limited. Moreover, we provide a proof that the proposed penalty method theoretically converges to a solution that corresponds to universal adversarial perturbations. We also demonstrate that it is possible to provide...
"Universal Adversarial Robustness of Texture and Shape-Biased Models"(ICIP'21) "Robustness and Transferability of Universal Attacks on Compressed Models"(AAAI'21 Workshop) We encourage you to explore these Python notebooks to generate and evaluate your own UAPs. If you are new to this topic, we...
adversarial_nets_lr_scheduler after_kernel agile_modeling al_for_fep albert algae_dice aloe alx amortized_bo android_control android_in_the_wild anthea aptamers_mlpd aqt aquadem ara_optimization arithmetic_sampling arxiv_latex_cleaner assemblenet assessment_plan_modeling attentional_adapters attribute_sem...