Attack detectionSmart gridRuzicka coefficientJaspen’s correlative stochasticConvolutional neural classifierSoft step activationThe deployment of 5G networks and IoT devices in smart grid applications provides
Illustration of the proposed replay attack detection neural network. The dark rectangle represents variable convolution, and the three internal parameters refer to the parameters of the CNN layer on the right side of Figure 2. First, the convolution kernel size is set to 5 by 5, and the step...
Journal of Intelligent Systems 2023; 32: 20220265 Research Article Dang-en Xie, Hai-na Hu, and Qiang Xu* Replay attack detection based on deformable convolutional neural network and temporal-frequency attention model https://doi.org/10.1515/jisys-2022-0265 received November 14, 2022; accepted ...
we investigate the significance of non-voiced audio segments and deep learning models like Convolutional Neural Networks (CNN) for audio replay attack detection. The non-voiced segments
The benefits of the suggested model are demonstrated by comparing the results obtained using the CNN-DWA approach with the Convolution Neural Network (CNN) method. The results of the experiments indicate that the suggested model has a higher accuracy (98.05%) than CNN (94.54%).Springer USMobile...
Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology. CNN is designed to automatically and adaptively
Pet dogs are our good friends. Realizing the dog’s emotions through the dog's facial expressions is beneficial to the harmonious coexistence between human beings and pet dogs. This paper describes a study on dog facial expression recognition using convo
在CVPR2020由中科院自动化研究所模式识别国家重点实验室主办的ChaLearnFace Anti-spoofing Attack Detection Challenge人脸防伪检测挑战赛中,由奥卢大学与明略科学院深度学习实验室等组成的团队,斩获多模态赛道冠军和单模态赛道亚军。 此次挑战赛中,奥卢大学和明略科学院团队运用的方法,主要来自于《Deep Spatial Gradient and...
A novel architecture for web-based attack detection using convolutional neural network. Comput. Secur. 100, 102096 (2021). Article Google Scholar Gupta, R., Patel, M. M., Shukla, A. & Tanwar, S. Deep learning-based malicious smart contract detection scheme for internet of things ...
These systems often struggle with scalability, manual feature extraction, and generalization to new attack patterns. To address these issues, this study proposes a Residual Network-based Convolutional Neural Network (ResNet-CNN) model to enhance the detection and classification of network intrusions. ...