Cover Image

Transferable Adversarial Attacks on SAM and Its Downstream Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Song, Yang, Wenhan, Yu, Yi, Lin, Xun, Ding, Henghui, Duan, Ling-Yu, Jiang, Xudong
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
by: Yu, Yi, et al.
Published: (2025)

Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
by: Yu, Yi, et al.
Published: (2024)

Time Is All It Takes: Spike-Retiming Attacks on Event-Driven Spiking Neural Networks
by: Yu, Yi, et al.
Published: (2026)

Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior
by: Yu, Yi, et al.
Published: (2024)

From Pretrain to Pain: Adversarial Vulnerability of Video Foundation Models Without Task Knowledge
by: Lu, Hui, et al.
Published: (2025)

Vulnerabilities in AI-generated Image Detection: The Challenge of Adversarial Attacks
by: Diao, Yunfeng, et al.
Published: (2024)

Boosting the Transferability of Adversarial Attacks with Global Momentum Initialization
by: Wang, Jiafeng, et al.
Published: (2022)

DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models
by: Sun, Ye, et al.
Published: (2026)

Improving the Transferability of Adversarial Attacks by an Input Transpose
by: Wan, Qing, et al.
Published: (2025)

Attacking Transformers with Feature Diversity Adversarial Perturbation
by: Gao, Chenxing, et al.
Published: (2024)

Stealthy Multi-Task Adversarial Attacks
by: Guo, Jiacheng, et al.
Published: (2024)

One Prompt to Verify Your Models: Black-Box Text-to-Image Models Verification via Non-Transferable Adversarial Attacks
by: Guo, Ji, et al.
Published: (2024)

Boosting Adversarial Transferability with Spatial Adversarial Alignment
by: Chen, Zhaoyu, et al.
Published: (2025)

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers
by: Cao, Hanwen, et al.
Published: (2025)

CAPAA: Classifier-Agnostic Projector-Based Adversarial Attack
by: Li, Zhan, et al.
Published: (2025)

AttackVLA: Benchmarking Adversarial and Backdoor Attacks on Vision-Language-Action Models
by: Li, Jiayu, et al.
Published: (2025)

Boosting Adversarial Transferability via Residual Perturbation Attack
by: Peng, Jinjia, et al.
Published: (2025)

Improving Transferability of Adversarial Examples via Bayesian Attacks
by: Li, Qizhang, et al.
Published: (2023)

Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability
by: Chen, Junxi, et al.
Published: (2024)

BadBlocks: Low-Cost and Stealthy Backdoor Attacks Tailored for Text-to-Image Diffusion Models
by: Wu, Jia, et al.
Published: (2025)

Natias: Neuron Attribution based Transferable Image Adversarial Steganography
by: Fan, Zexin, et al.
Published: (2024)

Region-Guided Attack on the Segment Anything Model (SAM)
by: Liu, Xiaoliang, et al.
Published: (2024)

Improving Adversarial Transferability with Neighbourhood Gradient Information
by: Guo, Haijing, et al.
Published: (2024)

Boosting Generative Adversarial Transferability with Self-supervised Vision Transformer Features
by: Wu, Shangbo, et al.
Published: (2025)

Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement
by: Ren, Yuchen, et al.
Published: (2025)

Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models
by: Zhang, Zongmin, et al.
Published: (2025)

Gungnir: Exploiting Stylistic Features in Images for Backdoor Attacks on Diffusion Models
by: Zhang, Lei, et al.
Published: (2025)

Membership Inference Attack Against Masked Image Modeling
by: Li, Zheng, et al.
Published: (2024)

MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
by: Qiu, Yixiang, et al.
Published: (2024)

Enabling Heterogeneous Adversarial Transferability via Feature Permutation Attacks
by: Wu, Tao, et al.
Published: (2025)

Reliable Disentanglement Multi-view Learning Against View Adversarial Attacks
by: Wang, Xuyang, et al.
Published: (2025)

Transferable Dual-Domain Feature Importance Attack against AI-Generated Image Detector
by: Zhu, Weiheng, et al.
Published: (2025)

ZIUM: Zero-Shot Intent-Aware Adversarial Attack on Unlearned Models
by: Yook, Hyun Jun, et al.
Published: (2025)

MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models
by: Wang, Yanting, et al.
Published: (2024)

MTL-UE: Learning to Learn Nothing for Multi-Task Learning
by: Yu, Yi, et al.
Published: (2025)

Transferability of Adversarial Attacks in Video-based MLLMs: A Cross-modal Image-to-Video Approach
by: Huang, Linhao, et al.
Published: (2025)

Snowball Adversarial Attack on Traffic Sign Classification
by: Etim, Anthony, et al.
Published: (2025)

Enhancing Adversarial Attacks: The Similar Target Method
by: Zhang, Shuo, et al.
Published: (2023)

Rethinking Robust Adversarial Concept Erasure in Diffusion Models
by: Yin, Qinghong, et al.
Published: (2025)

Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks
by: Zhang, Lei, et al.
Published: (2024)