Latest Articles for Adversarial Attacks

A method to identify attacks on systems combining images and text.

A new method helps identify weak points in deep learning models quickly.

A novel approach to ensure privacy while maintaining text utility in NLP models.

Super resolution techniques are complicating deepfake detection efforts significantly.

TrackPGD tests the limits of object tracking through advanced adversarial attacks.

A study on how VAEs perform across different demographic groups under attack.

New method improves neural network security using stochastic computing.

Exploring threats to DRL systems in cyber-physical energy management.

Examining the vulnerabilities of lightweight models against adversarial attacks.

New insights into robust classifiers enhance their ability to resist attacks.

This study reveals how non-adversarial attacks impact knowledge graph embedding algorithms.

Introducing HO-FMN for better evaluation of machine learning model robustness against adversarial attacks.

New method enhances adversarial attacks on 3D models using diffusion techniques.

Examining the vulnerabilities and potential attacks on NeRF technology.

Introducing a method to enhance AI system resilience through multi-task adversarial attacks.

Research reveals how friendly prompts can mislead AI systems.

Examining cybersecurity challenges and the role of AI in Industry 5.0.

Fast Preemption offers a proactive defense for deep learning systems against attacks.

A study on improving CNNs using partial labels and adversarial attack models.

This article reviews the weaknesses of multimodal models against various attack types.

Exploring the threats posed by adversarial attacks in medical imaging.

MALT improves adversarial attack efficiency and success in image classification models.

This article reviews methods to protect image quality systems from adversarial attacks.

A new method boosts the resilience of VAEs against tricky data manipulations.

Examining vulnerabilities in vision transformers and downstream models through transfer attacks.

Examining vulnerabilities and defenses in diffusion models for safe content generation.

Exploring the impact of adversarial attacks on explainability in deep learning.

New methods improve deep learning models' resistance to adversarial changes.

Addressing risks to MRI images in Alzheimer’s disease diagnosis through advanced detection methods.

Shuffling attacks reveal vulnerabilities in AI fairness assessments using methods like SHAP.

This article discusses improving the robustness of quantum machine learning models against adversarial attacks.

A new approach aims to improve active learning's resilience to attacks.

A new method targets multiple face authentication systems efficiently.

A new method uses makeup to enhance privacy in facial recognition systems.

Addressing the challenges of adversarial attacks on time series neural networks.

New methods improve machine learning models' defense against adversarial attacks.

New method uses IWMF to improve face recognition against adversarial attacks.

A new attack method undermines deepfake detection systems.

Improving botnet detection methods through machine learning and adversarial defense strategies.

Learn how watermarking secures AI models and supports creators' rights.