Network Intrusion Detection System: A systematic study of Machine Learning and Deep Learning approaches
Zeeshan Ahmad,Zeeshan Ahmad,Adnan Shahid Khan,Cheah Wai Shiang,Johari Abdullah,Farhan Ahmad,Farhan Ahmad +6 more
- Vol. 32, Iss: 1
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TLDR
The concept of IDS is clarified and the taxonomy based on the notable ML and DL techniques adopted in designing network‐based IDS (NIDS) systems is provided, which highlights various research challenges and provided the future scope for the research in improving ML andDL‐based NIDS.Abstract:
The rapid advances in the internet and communication fields have resulted in a huge increase in the network size and the corresponding data. As a result, many novel attacks are being gener...read more
Citations
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Journal ArticleDOI
Machine learning approaches to IoT security: A systematic literature review
Rasheed Ahmad,Izzat Alsmadi +1 more
TL;DR: This extensive literature survey on the most recent publications in IoT security identified a few key research trends that will drive future research in this field.
Journal ArticleDOI
HCRNNIDS: Hybrid Convolutional Recurrent Neural Network-Based Network Intrusion Detection System
TL;DR: A convolutional recurrent neural network (CRNN) is used to create a DL-based hybrid ID framework that predicts and classifies malicious cyberattacks in the network, and the proposed HCRNNIDS substantially outperforms current ID methodologies.
Journal ArticleDOI
Improving Performance of Autoencoder-Based Network Anomaly Detection on NSL-KDD Dataset
TL;DR: In this article, a 5-layer autoencoder-based model was proposed for network anomaly detection tasks based on the results obtained through an extensive and rigorous investigation of several performance indicators involved in an AE model.
Journal ArticleDOI
Botnet Attack Detection Using Local Global Best Bat Algorithm for Industrial Internet of Things
TL;DR: A Local-Global best Bat Algorithm for Neural Networks (LGBA-NN) to select both feature subsets and hyperparameters for efficient detection of botnet attacks, inferred from 9 commercial IoT devices infected by two botnets: Gafgyt and Mirai.
Journal ArticleDOI
Botnet Attack Detection by Using CNN-LSTM Model for Internet of Things Applications
TL;DR: In this paper, an accurate system to identify malicious attacks on the Internet of Things environment has become verifiable, which is used to detect cyber-attacks on IoT devices and to identify the malicious attacks.
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