Results 21 to 30 of about 79,418 (169)

Defense against Adversarial Swarms with Parameter Uncertainty [PDF]

open access: yesSensors, 2022
This paper addresses the problem of optimal defense of a high-value unit (HVU) against a large-scale swarm attack. We discuss multiple models for intra-swarm cooperation strategies and provide a framework for combining these cooperative models with HVU tracking and adversarial interaction forces.
Claire Walton   +4 more
openaire   +5 more sources

Adversarial Defense for Deep Speaker Recognition Using Hybrid Adversarial Training [PDF]

open access: yesICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Deep neural network based speaker recognition systems can easily be deceived by an adversary using minuscule imperceptible perturbations to the input speech samples. These adversarial attacks pose serious security threats to the speaker recognition systems that use speech biometric.
Pal, Monisankha   +5 more
openaire   +2 more sources

Continual Adversarial Defense

open access: yes, 2023
In response to the rapidly evolving nature of adversarial attacks against visual classifiers, numerous defenses have been proposed to generalize against as many known attacks as possible. However, designing a defense method that generalizes to all types of attacks is unrealistic, as the environment in which the defense system operates is dynamic.
Wang, Qian   +5 more
openaire   +2 more sources

Survey on adversarial attacks and defense of face forgery and detection

open access: yes网络与信息安全学报, 2023
Face forgery and detection has become a research hotspot.Face forgery methods can produce fake face images and videos.Some malicious videos, often targeting celebrities, are widely circulated on social networks, damaging the reputation of victims and ...
Shiyu HUANG, Feng YE, Tianqiang HUANG, Wei LI, Liqing HUANG, Haifeng LUO
doaj   +3 more sources

Adversarial Defense Via Local Flatness Regularization [PDF]

open access: yes2020 IEEE International Conference on Image Processing (ICIP), 2020
Adversarial defense is a popular and important research area. Due to its intrinsic mechanism, one of the most straightforward and effective ways of defending attacks is to analyze the property of loss surface in the input space. In this paper, we define the local flatness of the loss surface as the maximum value of the chosen norm of the gradient ...
Xu, Jia   +3 more
openaire   +2 more sources

Robust Rumor Detection based on Multi-Defense Model Ensemble

open access: yesApplied Artificial Intelligence, 2023
The development of adversarial technology, represented by adversarial text, has brought new challenges to rumor detection based on deep learning. In order to improve the robustness of rumor detection models under adversarial conditions, we propose a ...
Fan Yang, Shaomei Li
doaj   +1 more source

Adversarial Attacks Defense Method Based on Multiple Filtering and Image Rotation

open access: yesDiscrete Dynamics in Nature and Society, 2022
Adversarial examples in an image classification task cause neural networks to predict incorrect class labels with high confidence. Many applications related to image classification, such as self-driving and facial recognition, have been seriously ...
Feng Li, Xuehui Du, Liu Zhang
doaj   +1 more source

Adversarial attack and defense on graph neural networks: a survey

open access: yes网络与信息安全学报, 2021
For the numerous existing adversarial attack and defense methods on GNN, the main adversarial attack and defense algorithms of GNN were reviewed comprehensively, as well as robustness analysis techniques.Besides, the commonly used benchmark datasets and ...
Jinyin CHEN   +4 more
doaj   +3 more sources

Textual Adversarial Training Method Based on Distributed Perturbation [PDF]

open access: yesJisuanji gongcheng, 2023
Text adversarial defense aims to enhance the resilience of neural network models against different adversarial attacks. The current text confrontation defense methods are usually only effective against certain specific confrontation attacks and have ...
Zhidong SHEN, Hengxian YUE
doaj   +1 more source

Defending Against Adversarial Fingerprint Attacks Based on Deep Image Prior

open access: yesIEEE Access, 2023
Recently, deep learning-based biometric authentication systems, especially fingerprint authentication, have been used widely in real-world. However, these systems are vulnerable to adversarial attacks which prevent deep learning models from ...
Hwajung Yoo   +4 more
doaj   +1 more source

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