Results 121 to 130 of about 543,217 (204)

Adversarial Attacks on Data Attribution

open access: yesCoRR
Accepted at the 13th International Conference on Learning Representations (ICLR 2025)
Xinhe Wang 0001   +3 more
openaire   +4 more sources

Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition. [PDF]

open access: yesSensors (Basel), 2021
Lal S   +7 more
europepmc   +1 more source

Adversarial Risk Analysis: The Somali Pirates case [PDF]

open access: yes, 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]

open access: yes
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   +3 more
core  

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

open access: yesIET 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

Adversarial Attack Challenge for Secure Face Recognition 2025

open access: yes
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

ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks

open access: yes
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

Deep learning models for electrocardiograms are susceptible to adversarial attack. [PDF]

open access: yesNat Med, 2020
Han X   +5 more
europepmc   +1 more source

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