Latest Articles for Adversarial Examples

This article examines how adversarial examples affect malware detection systems.

This study examines how altering language affects text classifiers.

Examining SAM's robustness against adversarial attacks for safer self-driving technology.

Introducing DUCD, a privacy-focused method to protect DNNs from adversarial attacks.

A look at how AI can forget private data during image restoration.

Research focuses on generating adversarial examples to test credibility assessment systems.

A new approach for clearer visualization and understanding of deep learning models.

Research reveals vulnerabilities in AV lane detection through negative shadows.

A look into assessing the trustworthiness of AI explanations through adversarial sensitivity.

A new method enhances understanding and reliability of neural networks.

A study reveals vulnerabilities of DNA models to adversarial attacks.

Examining the risks and defenses of Multi-Modal Language Models in AI.

Exploring how irony confuses machine learning systems.

This article discusses the safety and security issues in multimodal AI systems.

New method enhances deep learning security with random neural fingerprints.

A closer look at claims of new image classification defense against adversarial examples.

Exploring the importance of individual classes in image classification models.

LLMs face challenges in detecting smart scams and need improvement.

Discover how NODE-AdvGAN tricks AI with subtle images.

Discover how adversarial examples challenge cybersecurity and the defenses against them.

Adversarial training improves AI's defense against deceptive attacks using the SDI measure.