Results 31 to 40 of about 527,315 (106)

A Simple Yet Efficient Method for Adversarial Word-Substitute Attack [PDF]

, 2022
NLP researchers propose different word-substitute black-box attacks that can fool text classification models. In such attack, an adversary keeps sending crafted adversarial queries to the target model until it can successfully achieve the intended ...
Li, Tianle, Yang, Yi
core   +1 more source

Adversarial Attack’s Impact on Machine Learning Model in Cyber-Physical Systems

, 2020
Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine Learning models used in a cloud data ...
Vähäkainu, Petri, Lehto, Martti, Kariluoto, Antti   +2 more
core   +1 more source

Attack Tree Analysis for Adversarial Evasion Attacks [PDF]

, 2023
Recently, the evolution of deep learning has promoted the application of machine learning (ML) to various systems. However, there are ML systems, such as autonomous vehicles, that cause critical damage when they misclassify.
Yamaguchi, Yuki, Aoki, Toshiaki
core  

Adversarial Attacks to Manipulate Target Localization of Object Detector

IEEE Access
Adversarial attack has gradually become an important branch in the field of artificial intelligence security, where the potential threat brought by adversarial example attack is more not to be ignored.
Kai Xu, Xiao Cheng, Ji Qiao, Jia-Teng Li, Kai-Xuan Ji, Jia-Yong Zhong, Peng Tian, Jian-Xun Mi   +7 more
doaj   +1 more source

Adversarial Robust and Explainable Network Intrusion Detection Systems Based on Deep Learning

Applied Sciences, 2022
The ever-evolving cybersecurity environment has given rise to sophisticated adversaries who constantly explore new ways to attack cyberinfrastructure. Recently, the use of deep learning-based intrusion detection systems has been on the rise. This rise is
Kudzai Sauka, Gun-Yoo Shin, Dong-Wook Kim, Myung-Mook Han   +3 more
doaj   +1 more source

Accelerated surgery versus standard care in hip fracture (HIP ATTACK): an international, randomised, controlled trial

, 2020
Observational studies have suggested that accelerated surgery is associated with improved outcomes in patients with a hip fracture.
(HIP ATTACK Investigators), Landoni G.
core   +1 more source

AB-VIP: Attack Method Using Brightness Information for Visibility Improvement of Adversarial Perturbations on the NMS Algorithm

IEEE Access
As with classification models, object detection models are vulnerable to adversarial attacks. In particular, adversarial attacks on key components of object detection models such as Region Proposal Network (RPN) and Non-Maximum Suppression (NMS ...
Gwang-Nam Kim, Han-Ju Lee, Han-Jin Lee, Hyeon-Jin Jung, Seok-Hwan Choi   +4 more
doaj   +1 more source

DTFA: Adversarial attack with discrete cosine transform noise and target features on deep neural networks

IET Image Processing, 2023
Image recognition on deep neural network is vulnerable to adversarial sample attacks. The adversarial attack accuracy is low when only limited queries on the target are allowed with the current black box environment.
Dong Yang, Wei Chen, Songjie Wei
doaj   +1 more source

Towards Adversarial Attack on Vision-Language Pre-training Models

, 2022
While vision-language pre-training model (VLP) has shown revolutionary improvements on various vision-language (V+L) tasks, the studies regarding its adversarial robustness remain largely unexplored.
Sang, Jitao, Zhang, Jiaming, Yi, Qi
core  

A Two-Stage Generative Adversarial Networks With Semantic Content Constraints for Adversarial Example Generation

IEEE Access, 2020
Deep neural networks (DNNs) have achieved great success in various applications due to their strong expressive power. However, recent studies have shown that DNNs are vulnerable to adversarial examples, and these manipulated instances can mislead DNN ...
Jianyi Liu, Yu Tian, Ru Zhang, Youqiang Sun, Chan Wang   +4 more
doaj   +1 more source