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Bibliografiske detaljer
Main Authors:	Maag, Kira, Resner, Roman, Fischer, Asja
Format:	Preprint
Udgivet:	2024
Fag:	Computer Vision and Pattern Recognition Cryptography and Security
Online adgang:	https://arxiv.org/abs/2408.10021
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Lignende værker

Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation
af: Maag, Kira, et al.
Udgivet: (2023)

Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation
af: Maag, Kira, et al.
Udgivet: (2023)

Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models
af: Müller, Andreas, et al.
Udgivet: (2024)

Towards A Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models
af: Thietke, Jonas, et al.
Udgivet: (2025)

SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation
af: Gehrmann, Christian, et al.
Udgivet: (2026)

AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection
af: Meng, Xiangtao, et al.
Udgivet: (2023)

False Negative Reduction in Video Instance Segmentation using Uncertainty Estimates
af: Maag, Kira
Udgivet: (2021)

XAI-Based Detection of Adversarial Attacks on Deepfake Detectors
af: Pinhasov, Ben, et al.
Udgivet: (2024)

Delving into Decision-based Black-box Attacks on Semantic Segmentation
af: Chen, Zhaoyu, et al.
Udgivet: (2024)

ConSeg: Contextual Backdoor Attack Against Semantic Segmentation
af: Abbasi, Bilal Hussain, et al.
Udgivet: (2025)

Signal Adversarial Examples Generation for Signal Detection Network via White-Box Attack
af: Li, Dongyang, et al.
Udgivet: (2024)

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

AdvART: Adversarial Art for Camouflaged Object Detection Attacks
af: Guesmi, Amira, et al.
Udgivet: (2023)

Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving
af: Zheng, Junhao, et al.
Udgivet: (2024)

RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering
af: Hull, Matthew, et al.
Udgivet: (2024)

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

Optical Lens Attack on Deep Learning Based Monocular Depth Estimation
af: Zhou, Ce, et al.
Udgivet: (2024)

Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
af: Lorenz, Peter, et al.
Udgivet: (2022)

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

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

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

Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation
af: Du, Xia, et al.
Udgivet: (2025)

VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models
af: Yin, Ziyi, et al.
Udgivet: (2023)

Query-Efficient Video Adversarial Attack with Stylized Logo
af: Tang, Duoxun, et al.
Udgivet: (2024)

Fall Leaf Adversarial Attack on Traffic Sign Classification
af: Etim, Anthony, et al.
Udgivet: (2024)

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

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

Integrating uncertainty quantification into randomized smoothing based robustness guarantees
af: Däubener, Sina, et al.
Udgivet: (2024)

Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey
af: Zhang, Chiyu, et al.
Udgivet: (2024)

Enhanced Hybrid Deep Learning Approach for Botnet Attacks Detection in IoT Environment
af: kumar, A. Karthick, et al.
Udgivet: (2025)

Detection of Adversarial Attacks in Robotic Perception
af: Sharawy, Ziad, et al.
Udgivet: (2026)

Attack Anything: Blind DNNs via Universal Background Adversarial Attack
af: Lian, Jiawei, et al.
Udgivet: (2024)

Backdoor Mitigation in Object Detection via Adversarial Fine-Tuning
af: Dunnett, Kealan, et al.
Udgivet: (2026)

Adversarial Attack On Yolov5 For Traffic And Road Sign Detection
af: Jain, Sanyam
Udgivet: (2023)

Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks
af: Chattopadhyay, Nandish, et al.
Udgivet: (2024)

Time Traveling to Defend Against Adversarial Example Attacks in Image Classification
af: Etim, Anthony, et al.
Udgivet: (2024)

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

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

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

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