Generation and Countermeasures of adversarial examples on vision

Towards Efficient Adversarial Training on Vision Transformers

Such a design will better preserve the feed-forward process and therefore guard the back- ward gradient computation of generating the adversarial examples. As ...

Adversarial Attacks and Defenses in Images, Graphs and Text

In this survey, we review the state of the art algorithms for generating adversarial examples and the countermeasures against adversarial examples.

Adversarial Examples in Visual Object Tracking in Satellite Videos

FGSM is a gradient-based adversarial examples generation method. It can be expressed as Formula (1). In Formula (1), x is the input of the neural network model, ...

16 A General Framework for Adversarial Examples with Objectives

Our framework builds on recent work in generative adversarial networks. (GANs) [25] to train an attack generator, i.e., a neural network that can generate ...

Adversarial Machine Learning | Attacks and Defense Methods - Saiwa

Adversarial examples are meticulously constructed through the introduction of minute, meticulously calculated perturbations to the input data.

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.

Adversarial Vision Challenge - mediaTUM

For black-box adversarial examples generation, we use return-early L2 iterative transfer attack with step = 10. All experiments were run using batch size. 50 ...

Spatially Transformed Adversarial Examples - OpenReview

We propose a new approach for generating adversarial examples based on spatial transformation, which produces perceptually realistic examples compared to ...

Adversarial machine learning - Wikipedia

Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. A survey from May 2020 ...

Trustworthy-AI-Group/Adversarial_Examples_Papers: A list of recent ...

AnyAttack: Towards Large-scale Self-supervised Generation of Targeted Adversarial Examples for Vision-Language Models. Jiaming Zhang, Junhong Ye, Xingjun Ma ...

Boosting the Transferability of Video Adversarial Examples via ...

By generating adversarial exam- ples over translated videos, the resulting adversarial examples are less sensitive to temporal patterns existed in the white-.

Adversarial Examples: Attacks and Defenses for Deep Learning

Adversarial examples are imperceptible to human but can easily fool deep neural networks in the testing/deploying stage. The vulnerability to adversarial ...

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.

An Overview of Adversarial Attacks and Defenses

Such adversarial examples have higher confidence, better portability and robustness. The authors show that this method can be combined with the structural ...

Senior Software Engineer and Researcher - Ignited Minds Journals

... generating adversarial examples and countermeasures in neural networks. ... From computer vision to speech recognition to natural language processing (NLP), ...

Adversarial Machine Learning: A Taxonomy and Terminology of ...

methods for optimizing the generation of adversarial examples with the goals of minimizing ... In computer vision applications, adversarial ...

Robustness and Adversarial Attacks in Computer Vision

Robustness Improvement: Moreover, by training on a numerous set of adversarial examples, models are capable of tuning in to perceive slight ...

Adversarial Email Generation against Spam Detection Models ...

For example, recent works in computer vision use gradient-based methods [1], ... Tan, “Generating adversarial malware examples for black-box attacks based on ...

Adversarial Examples: Attacks and Defenses for Deep Learning

We further elaborate on countermeasures for adversarial examples. In ... Most defenses target adversarial examples in the computer vision task. However ...

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

AnyAttack: Towards Large-scale Self-supervised Generation of Targeted Adversarial Examples for Vision-Language Models. ... countermeasures against such attacks.