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Multi-View Fusion Based for Intrusion Detection with Deep Learning Architectures

https://doi.org/10.2139/ssrn.4862751
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inferredcites →https://doi.org/10.1007/bf00344251openalex-extracted
Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
inferredcites →https://doi.org/10.1007/s10207-023-00661-7openalex-extracted
P2ADF: a privacy-preserving attack detection framework in fog-IoT environment
inferredcites →https://doi.org/10.1007/s10922-021-09589-6openalex-extracted
AS-IDS: Anomaly and Signature Based IDS for the Internet of Things
inferredcites →https://doi.org/10.1016/j.engappai.2022.105670openalex-extracted
RepuTE: A soft voting ensemble learning framework for reputation-based attack detection in fog-IoT milieu
inferredcites →https://doi.org/10.1016/j.jisa.2022.103248openalex-extracted
Multi-datasource machine learning in intrusion detection: Packet flows, system logs and host statistics
inferredcites →https://doi.org/10.1016/j.measurement.2016.10.031openalex-extracted
Anomaly detection based on uncertainty fusion for univariate monitoring series
inferredcites →https://doi.org/10.1016/j.measurement.2017.05.034openalex-extracted
A hybrid intrusion detection system for virtual jamming attacks on wireless networks
inferredcites →https://doi.org/10.1016/j.measurement.2019.107450openalex-extracted
Robust detection for network intrusion of industrial IoT based on multi-CNN fusion
inferredcites →https://doi.org/10.1016/j.neucom.2017.12.029openalex-extracted
Multi-View Least Squares Support Vector Machines Classification
inferredcites →https://doi.org/10.1016/j.neucom.2021.03.090openalex-extracted
Deep multi-view learning methods: A review
inferredcites →https://doi.org/10.1109/access.2017.2762418openalex-extracted
A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/access.2018.2863036openalex-extracted
Enhanced Network Anomaly Detection Based on Deep Neural Networks
inferredcites →https://doi.org/10.1109/access.2021.3120626openalex-extracted
Intrusion Detection System Using Machine Learning for Vehicular Ad Hoc Networks Based on ToN-IoT Dataset
inferredcites →https://doi.org/10.1109/iccv.2015.114openalex-extracted
Multi-view Convolutional Neural Networks for 3D Shape Recognition
inferredcites →https://doi.org/10.1109/pccc.2018.8710993openalex-extracted
A Novel Intrusion Detection Algorithm for Industrial Control Systems Based on CNN and Process State Transition
inferredcites →https://doi.org/10.1109/tetci.2017.2772792openalex-extracted
A Deep Learning Approach to Network Intrusion Detection
inferredcites →https://doi.org/10.1109/tkde.2020.3048678openalex-extracted
Cross-View Locality Preserved Diversity and Consensus Learning for Multi-View Unsupervised Feature Selection
inferredcites →https://doi.org/10.1109/tsmcb.2012.2212243openalex-extracted
An Efficient Approach to Integrating Radius Information into Multiple Kernel Learning
inferredcites →https://doi.org/10.1515/9781400874668openalex-extracted
Adaptive Control Processes
inferredcites →https://doi.org/10.18653/v1/w19-4301openalex-extracted
Deep Generalized Canonical Correlation Analysis
inferredcites →https://doi.org/10.3390/electronics10111257openalex-extracted
Deep Learning-Based Intrusion Detection for Distributed Denial of Service Attack in Agriculture 4.0
inferredcites →https://doi.org/10.3390/electronics13061053openalex-extracted
IoT-Based Intrusion Detection System Using New Hybrid Deep Learning Algorithm
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