Results 291 to 300 of about 96,849 (322)
SecMLOps: A comprehensive framework for integrating security throughout the machine learning operations lifecycle. [PDF]
Empir Softw EngZhang X, Zhao P, Jaskolka J, Li H, Lu R.
europepmc +1 more source
FP-ZOO: Fast Patch-Based Zeroth Order Optimization for Black-Box Adversarial Attacks on Vision Models. [PDF]
Sensors (Basel)Seo J, Jeon S.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Adversarial Attacks on Genotype Sequences
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022ABSTRACT Adversarial attacks can drastically change the output of a method by performing a small change on its input. While they can be a useful framework to analyze worst-case robustness, they can also be used by malicious agents to perform damage in machine learning-based applications.
Daniel Mas Montserrat +1 more
openaire +1 more source
Adversarial Attack on Video Retrieval
2020 The 4th International Conference on Video and Image Processing, 2020Recently adversarial examples have been reported to reveal the fragility of deep learning models. However, most adversarial attacks focus on classification task and less attention has been paid to retrieval task. In this paper, we are the first to investigate adversarial examples on the video retrieval system in both non-targeted and targeted attack ...
Ying Zou 0008 +2 more
openaire +1 more source
Adversarial Attack? Don't Panic
2018 4th International Conference on Big Data Computing and Communications (BIGCOM), 2018Deep learning is playing a more and more important role in our daily life and scientific research such as autonomous systems, intelligent life and data mining. However, numerous studies have showed that deep learning with superior performance on many tasks may suffer from subtle perturbations constructed by attacker purposely, called adversarial ...
Feixia Min, Xiaofeng Qiu, Fan Wu
openaire +1 more source
Generative Transferable Adversarial Attack
Proceedings of the 3rd International Conference on Video and Image Processing, 2019Despite their superior performance in computer vision tasks, deep neural networks are found to be vulnerable to adversarial examples, slightly perturbed examples that can mislead trained models. Moreover, adversarial examples are often transferable, i.e., adversaries crafted for one model can attack another model.
Yifeng Li +3 more
openaire +1 more source
A Survey of Adversarial Attack and Defense Methods for Malware Classification in Cyber Security
IEEE Communications Surveys and Tutorials, 2023Senming Yan, Wei Wang, Limin Sun
exaly
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Xiaolin Huang +2 more
exaly