Papers with Code 아카이브

Adversarial Attack

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 4
평가표: 3
보존된 평가 기록: 9

An Adversarial Attack is a technique to find a perturbation that changes the prediction of a machine learning model. The perturbation can be very small and imperceptible to human eyes.

Source: Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/HanxunH/XTransferBench

Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations

https://github.com/HowToMakeABomb101/Hot2MakeAB0mbSite

The Limitations of Deep Learning in Adversarial Settings

https://github.com/I-am-Bot/DeepRobust

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

https://github.com/I-am-Bot/RobustTorch

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

https://github.com/IBM/Autozoom-Attack

ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models

https://github.com/IBM/EAD-Attack

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

https://github.com/IBM/ZOO-Attack

ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models

https://github.com/Jason-J-Choi/DeBERTa_TxtClassifier

Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment

https://github.com/Jayfeather1024/Backdoor-Enhanced-Alignment

Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment

https://github.com/Jeffkang-94/pytorch-adversarial-attack

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/Jiawei955/detection-of-physical-adversarial-attack

AdvHat: Real-world adversarial attack on ArcFace Face ID system

https://github.com/Jupetus/ExplainableAI

Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks

https://github.com/KanikaNegi/text-to-image-using-GAN

Generative Adversarial Text to Image Synthesis

https://github.com/KatherineBaq/NMA-CN2021-fMRI_vs_DNNs

Controversial stimuli: pitting neural networks against each other as models of human recognition

https://github.com/KatyaKom/Python-Z3-NNVerif

Safety Verification of Deep Neural Networks

https://github.com/KevinHuang841006/AI_Security_training

Towards Evaluating the Robustness of Neural Networks

https://github.com/KnowledgeDiscovery/FaceSec

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/LTS4/SparseFool

DeepFool: a simple and accurate method to fool deep neural networks

https://github.com/LeMinhThong/blackbox-attack

Towards Evaluating the Robustness of Neural Networks

https://github.com/LiangSiyuan21/BadCLIP

BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive Learning

https://github.com/Linear95/CLUB

Deep Variational Information Bottleneck

https://github.com/Mark12Ding/GNN-Practical-Attack

Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem

https://github.com/MashmallowWoR/AdversarialDeformation

ADef: an Iterative Algorithm to Construct Adversarial Deformations

https://github.com/Maymaher/StackGANv2

Generative Adversarial Text to Image Synthesis

https://github.com/Mckinsey666/Conditional-GAN-Anime-Generation

Generative Adversarial Text to Image Synthesis

https://github.com/Mind23-2/MindCode-101/tree/main/MTCNN

Real-world adversarial attack on MTCNN face detection system

https://github.com/Mind23-2/MindCode-3/tree/main/MTCNN

Real-world adversarial attack on MTCNN face detection system

https://github.com/MindCode-4/code-11/tree/main/Adversarial-Laser-Spot

Adversarial Laser Spot: Robust and Covert Physical-World Attack to DNNs

https://github.com/MindSpore-paper-code-2/code400/tree/main/Arcface

AdvHat: Real-world adversarial attack on ArcFace Face ID system

https://github.com/MindSpore-paper-code-3/code9/tree/main/Arcface

AdvHat: Real-world adversarial attack on ArcFace Face ID system

https://github.com/MindSpore-scientific-2/code-2/tree/main/signSGD

SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding

https://github.com/MindSpore-scientific-2/code-4/tree/main/Least_Generative

Generative Adversarial Text to Image Synthesis

https://github.com/MindSpore-scientific-2/code-8/tree/main/signSGD

SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding

https://github.com/MindSpore-scientific/code-3/tree/main/Adversarial-Laser-Spot

Adversarial Laser Spot: Robust and Covert Physical-World Attack to DNNs

https://github.com/Mrzhang3389/MTCNN

Real-world adversarial attack on MTCNN face detection system

https://github.com/Muzammal-Naseer/Improving-Adversarial-Transferability-of-Vision-Transformers

On Improving Adversarial Transferability of Vision Transformers

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.