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A Security Study of Multimodel Artificial Intelligence System: Adaptive Retention Attack for Object Detection System with Multifocus Image Fusion Model

Advanced Intelligent Systems
Image preprocessing models are usually employed as the preceding operations of high‐level vision tasks to improve the performance. The adversarial attack technology makes both these models face severe challenges.
Xueshuai Gao +6 more
doaj +1 more source

Traffic adversarial example attack and defense method based on explainable artificial intelligence

Tongxin xuebao
An adversarial example attack method based on XAI was proposed for AI-based NIDS. By identifying critical perturbation features with XAI and applying targeted perturbations while preserving traffic functionality, malicious traffic was gradually altered ...
MA Bowen +4 more
doaj

Superclass Adversarial Attack

, 2022
Adversarial attacks have only focused on changing the predictions of the classifier, but their danger greatly depends on how the class is mistaken. For example, when an automatic driving system mistakes a Persian cat for a Siamese cat, it is hardly a ...
Yamasaki, Toshihiko, Kera, Hiroshi, Kumano, Soichiro +2 more
core

Breaking and Healing: GAN-Based Adversarial Attacks and Post-Adversarial Recovery for 5G IDSs

IEEE Access
Generative adversarial networks (GANs) have advanced rapidly in data augmentation and generation, and researchers have been exploring their applications in other areas, including adversarial attack generation.
Yasmeen Alslman +2 more
doaj +1 more source

Adversarial Risk Analysis: The Somali Pirates case [PDF]

, 2013
Some of the current world’s biggest problems revolve around security issues. This has raised recent interest in resource allocation models to manage security threats, from terrorism to organized crime through money laundering.
Ríos, Jesús, Ríos Insúa, David
core

SA-Attack: Speed-adaptive stealthy adversarial attack on trajectory prediction [PDF]

Trajectory prediction is critical for the safe planning and navigation of automated vehicles. The trajectory prediction models based on the neural networks are vulnerable to adversarial attacks.
Yin, Huilin, Li, Jiaxiang, Zhen, Pengju, Yan, Jun +3 more
core

Adversarial Attack Challenge for Secure Face Recognition 2025

Adversarial attacks pose a significant threat to the reliability of biometric systems, particularly in security-critical applications such as identity verification and access control.
Nicolas Göller +15 more
core +1 more source

AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch

, 2021
AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial ...
Shengshan Hu (13429977) +5 more
core

A knowledge distillation strategy for enhancing the adversarial robustness of lightweight automatic modulation classification models

IET Communications
Automatic modulation classification models based on deep learning models are at risk of being interfered by adversarial attacks. In an adversarial attack, the attacker causes the classification model to misclassify the received signal by adding carefully
Fanghao Xu +5 more
doaj +1 more source

ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks

Existing self-supervised adversarial training (self-AT) methods rely on hand-crafted adversarial attack strategies for PGD attacks, which fail to adapt to the evolving learning dynamics of the model and do not account for instance-specific ...
Saini, Rajkumar +5 more
core +1 more source

adversarial attacks
adversarial example
machine learning

adversarial examples
deep learning
object detection

generative adversarial networks