In this paper, based on facial landmark approaches, the possible vulnerability of ensemble algorithms to the FGSM attack has been assessed using three commonly used models: convolutional neural network-based antialiasing (A_CNN), Xc_Deep2-based DeepLab v2, and SqueezeNet (Squ_Net)-based Fire ...
sample_targeted_attacks/iter_target_class/- iterative target class attack. This is a pretty good white-box attack, but it does not do well in black box setting. sample_defenses/- directory with examples of defenses: sample_defenses/base_inception_model/- baseline inception classifier, which actu...
sample_targeted_attacks/iter_target_class/ - iterative target class attack. This is a pretty good white-box attack, but it does not do well in black box setting. sample_defenses/ - directory with examples of defenses: sample_defenses/base_inception_model/ - baseline inception classifier, which...
usp=sharing>`__.## In[9]:epsilons = [0, .05, .1, .15, .2, .25, .3]pretrained_model = "data/lenet_mnist_model.pth"use_cuda=True# Model Under Attack# ~~~## As mentioned, the model under attack is the same MNIST model from# `pytorch/examples/mnist <https://github.com/py...
2020年最新对抗攻击论文泛读 adversarial attack robustness 思想: 分析了FGSM,I-FGSM,MI-FGSM,PGD,CW等方法,指出了固定步长在复杂边界处的不足:因为固定步长对抗样本是非固定步长的一个很小的子集,因此提出Ada-FGSM。算法...,DeepFool,etl)获取几张不同的图的攻击成功的样本,将其组合成矩阵,对矩阵进行主成分分析...
security deep-learning attack tensorflow paper intel dnn shield defense georgia-tech vaccination adversarial-machine-learning imagenet-dataset fgsm video-demo jpeg-compression carlini-wagner i-fgsm deepfool Updated Mar 24, 2023 Python edosedgar / mtcnnattack Star 71 Code Issues Pull requests The...
This implementation is part of the paper entitled "Attack Analysis of Face Recognition Authentication Systems Using Fast Gradient Sign Method", published in the International Journal of Applied Artificial Intelligence by Taylor & Francis. machine-learning authentication artificial-intelligence biometrics face-...
A pytorch implentation of FGSM attack method in a paper https://arxiv.org/abs/1412.6572x ′ = x + ε s i g n ( ▽ x J ( θ , x , y ) ) UsageI trained simple fully-connected model (28*28 -> 1000 -> 500 -> 10) using MNIST dataset and save checkpoint in modelsave ...
However, adv.PGD requires too much training time since the projected gradient attack (PGD) takes multiple iterations to generate perturbations. On the other hand, adversarial training with the fast gradient sign method (adv.FGSM) takes much less training time since the fast gradient sign method (...
基于Ｇｒａｄ ＣＡＭ的Ｍａｓｋ ＦＧＳＭ对抗样本攻击 余莉萍 （复旦大学计算机科学技术学院 上海２０１２０３）收稿日期：２０２０－０１－１５。余莉萍，硕士生，主研领域：人工智能与认知科学。摘 要 深度学习缺乏可解释性，其容易受到对抗性样本的攻击。对此引入一种深度学习可解释性模型Ｇｒａｄ ＣＡＭ（Ｇｒａ...