Results 241 to 250 of about 94,861 (274)

Detecting chaos in adversarial examples

Chaos, Solitons & Fractals, 2022
Oscar Deniz, Anibal Pedraza, Gloria Bueno   +2 more
openaire   +1 more source

Detecting adversarial examples using surrogate models

2020
Deep Learning, als Teilbereich des maschinellen Lernens, hat in den letzten Jahren erhebliche Fortschritte erzielt.Durch die zunehmende Integration in Anwendungen, besonders im Gebiet der Bildverarbeitung und Mustererkennung durch Convolutional Neural Networks (CNN), ist es immer stärker in unser tägliches Leben integriert.
openaire   +1 more source

Towards robust classification detection for adversarial examples

2020 15th International Conference for Internet Technology and Secured Transactions (ICITST), 2020
In the field of computer vision, machine learning (ML) models have been widely used in various tasks to achieve better performance. ML models, however, do a poor job of identifying malicious inputs such as adversarial examples. Abuse adversarial examples can cause security threats in ML-based products or applications.
Huangxiaolie Liu, Dong Zhang, Huijun Chen   +2 more
openaire   +1 more source

Adversarial example generation using object detection

7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 2022
Liang Gu, Haitao Liu, Xin Gong, Yi An, Ning Yu, Jing Duan, Jie Duan   +6 more
openaire   +1 more source

Feature autoencoder for detecting adversarial examples

International Journal of Intelligent Systems, 2022
Hongwei Ye, Xiaozhang Liu
openaire   +1 more source

DeepSHAP Summary for Adversarial Example Detection

2023 IEEE/ACM International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest), 2023
Yi-Ching Lin, Fang Yu
openaire   +1 more source

IIoT Deep Malware Threat Hunting: From Adversarial Example Detection to Adversarial Scenario Detection

IEEE Transactions on Industrial Informatics, 2022
Bardia Esmaeili, Amin Azmoodeh, Ali Dehghantanha, Hadis Karimipour, Behrouz Zolfaghari, Mohammad Hammoudeh   +5 more
openaire   +1 more source

Adversarial Machine Learning in Wireless Communications Using RF Data: A Review

IEEE Communications Surveys and Tutorials, 2023
Damilola Adesina, Yalin E Sagduyu, Lijun Qian   +2 more
exaly  

Generative Adversarial Networks (GANs)

ACM Computing Surveys, 2022
Divya Saxena, Jiannong Cao
exaly  

Multi-Modal Adversarial Example Detection with Transformer

2022 International Joint Conference on Neural Networks (IJCNN), 2022
Chaoyue Ding, Shiliang Sun, Jing Zhao
openaire   +1 more source