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IMIDS: An Intelligent Intrusion Detection System against Cyber Threats in IoT

https://doi.org/10.3390/electronics11040524

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Multi-classification of UNSW-NB15 Dataset for Network Anomaly Detection System

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Intrusion Detection Using Deep Neural Network with AntiRectifier Layer

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A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges

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Dendron : Genetic trees driven rule induction for network intrusion detection systems

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inferredcites →https://doi.org/10.1016/j.net.2020.05.012openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.procs.2020.03.330openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.procs.2021.04.118openalex-snapshot

attackGAN: Adversarial Attack against Black-box IDS using Generative Adversarial Networks

inferredcites →https://doi.org/10.1016/j.swevo.2019.100631openalex-snapshot

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inferredcites →https://doi.org/10.1109/access.2018.2844794openalex-snapshot

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inferredcites →https://doi.org/10.1109/compsac48688.2020.0-218openalex-snapshot

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inferredcites →https://doi.org/10.1109/dasc-picom-datacom-cyberscitec.2016.32openalex-snapshot

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inferredcites →https://doi.org/10.1109/dcoss.2019.00059openalex-snapshot

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inferredcites →https://doi.org/10.1109/globalsip.2018.8646424openalex-snapshot

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inferredcites →https://doi.org/10.1109/icasi.2018.8394474openalex-snapshot

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inferredcites →https://doi.org/10.1109/iccws48432.2020.9292388openalex-snapshot

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inferredcites →https://doi.org/10.1109/icissec.2016.7885853openalex-snapshot

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inferredcites →https://doi.org/10.1109/ictcs.2017.29openalex-snapshot

Experimental Evaluation of a Multi-layer Feed-Forward Artificial Neural Network Classifier for Network Intrusion Detection System

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inferredcites →https://doi.org/10.1109/jiot.2020.3048439openalex-snapshot

Application Domains, Evaluation Data Sets, and Research Challenges of IoT: A Systematic Review

inferredcites →https://doi.org/10.1109/mc.2017.201openalex-snapshot

DDoS in the IoT: Mirai and Other Botnets

inferredcites →https://doi.org/10.1109/netsoft51509.2021.9492685openalex-snapshot

Intrusion Detection using Network Traffic Profiling and Machine Learning for IoT

inferredcites →https://doi.org/10.1109/ntms.2019.8763842openalex-snapshot

A Novel Online Incremental Learning Intrusion Prevention System

inferredcites →https://doi.org/10.1109/tkde.2008.239openalex-snapshot

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inferredcites →https://doi.org/10.1109/tsusc.2018.2808430openalex-snapshot

Generalized Outlier Gaussian Mixture Technique Based on Automated Association Features for Simulating and Detecting Web Application Attacks

inferredcites →https://doi.org/10.1109/wcnc.2018.8376973openalex-snapshot

Cyberattack detection in mobile cloud computing: A deep learning approach

inferredcites →https://doi.org/10.1109/wowmom.2015.7158207openalex-snapshot

Experiments with security and privacy in IoT networks

inferredcites →https://doi.org/10.1145/3299815.3314439openalex-snapshot

Intrusion Detection Using Big Data and Deep Learning Techniques

inferredcites →https://doi.org/10.1145/3424155openalex-snapshot

On Generating Network Traffic Datasets with Synthetic Attacks for Intrusion Detection

inferredcites →https://doi.org/10.1155/2020/4586875openalex-snapshot

A Stacking Ensemble for Network Intrusion Detection Using Heterogeneous Datasets

inferredcites →https://doi.org/10.12783/dtetr/iceta2017/19916openalex-snapshot

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inferredcites →https://doi.org/10.12785/ijcds/080505openalex-snapshot

Network Based Intrusion Detection Using the UNSW-NB15 Dataset

inferredcites →https://doi.org/10.14569/ijacsa.2017.080651openalex-snapshot

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inferredcites →https://doi.org/10.3390/electronics9040577openalex-snapshot

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An Enhanced Intrusion Detection System Using Attention-Based Stacked Sparse Autoencoder Feature Extraction

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Enhancing Multi-Agent Reinforcement Learning Intrusion Detection Systems Using Random Forest Q-Value Estimation

inferred← citeshttps://doi.org/10.5935/jetia.v10i47.1096openalex-snapshot

Enhancing iot network security through advanced data preprocessing and hybrid firefly-salp swarm optimized deep cnn-based intrusion detection

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