Generation and Countermeasures of adversarial examples on vision

In this survey, we reviewed the existence, generation, and countermeasures of adversarial examples in Computer Vision, to provide comprehensive coverage of the ...

(PDF) Generation and Countermeasures of adversarial examples on ...

In this survey, we reviewed the existence, generation, and countermeasures of adversarial examples in Computer Vision, to provide comprehensive ...

Generation and Countermeasures of adversarial examples on vision ...

Generation and Countermeasures of adversarial examples on vision: a survey. Jiangfan Liu 1, 2. ,. Yishan Li 1. ,. Yanming Guo 1. ,. Yu Liu 3. ,. Jun Tang 1. ,.

Generation and Countermeasures of adversarial examples on vision ...

In this survey, we reviewed the existence, generation, and countermeasures of adversarial examples in Computer Vision, to provide comprehensive coverage of the ...

This survey is organized around three key aspects, which conclude ...

This survey is organized around three key aspects, which conclude the hypothesis, generation, and countermeasures of adversarial examples ... This survey is ...

Adversarial Attacks and Countermeasures on Image Classification ...

Recency: Recent articles in adversarial machine learning (AML) [88] research are prioritized using a time constraint, focusing on the last 10 ...

AnyAttack: Towards Large-scale Self-supervised Generation ... - arXiv

Title:AnyAttack: Towards Large-scale Self-supervised Generation of Targeted Adversarial Examples for Vision-Language Models ; Subjects: Machine ...

Towards transferable adversarial attacks on vision transformers for ...

In this paper, we propose a Forward-Backward Transferable Adversarial Attack framework (FBTA) that can generate highly transferable adversarial examples ...

The Adversarial Attacks Threats on Computer Vision: A Survey

The threat raises the severe security problem in deep learning applications. This study aims to summarize recent research for generating adversarial examples in ...

Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey

The research community currently needs: 1) unified insights into adversariality, transferability, and generalization; 2) detailed evaluations of ...

[PDF] Adversarial Examples: Opportunities and Challenges

The concept, cause, characteristics, and evaluation metrics of AEs are introduced, then a survey on the state-of-the-art AE generation methods with the ...

Adversarial Attack and Defense: A Survey - MDPI

In recent years, deep neural network (DNN) has been widely used in computer vision [1,2,3], speech recognition [4,5,6], NLP [7,8] and many other ...

A novel and universal GAN-based countermeasure to recover ...

Then, we defend against seven types of state-of-the-art adversarial examples on four deep neural networks and compare them with six existing countermeasures.

The Generation of Visually Credible Adversarial Examples with ...

Prior research has offered readers visual comparisons of a small number of authentic inputs and their AEs (e.g., Madry et al. [2017]) and ...

Decision-based Black-box Attack Against Vision Transformers via ...

These two properties in noise sensitivity make it extremely difficult for existing decision-based attacks to find adversarial examples with small noise.

A Review of Adversarial Attack and Defense for Classification Methods

54 Citations · Generation and Countermeasures of adversarial examples on vision: a survey · PSI Analysis of Adversarial-Attacked DCNN Models · Benchmarking ...

Generating Adversarial Examples via Attribute-conditioned Image ...

Semantic image editing. Semantic image synthesis and manipulation is a pop- ular research topic in machine learning, graphics and vision. Thanks to recent.

Adversarial Example Generation - PyTorch

This tutorial will raise your awareness to the security vulnerabilities of ML models, and will give insight into the hot topic of adversarial machine learning.

On the Robustness of Vision Transformers to Adversarial Examples

Broadly speaking, an attacker creates an adversarial example using one of two threat models. Under a white-box adversary [5], the attacker has access to the ...

10.4 Adversarial Examples | Interpretable Machine Learning

An adversarial example is an instance with small, intentional feature perturbations that cause a machine learning model to make a false prediction.