A hybrid CNN+LSTM-based intrusion detection system for industrial IoT networks

Ondokuz Mayıs University · Sakarya University · +1 more institution

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Abstract

The Internet of Things (IoT) ecosystem has proliferated based on the use of the internet and cloud-based technologies in the industrial area. IoT technology used in the industry has become a large-scale network based on the increasing amount of data and number of devices. Industrial IoT (IIoT) networks are intrinsically unprotected against cyber threats and intrusions. It is, therefore, significant to develop Intrusion Detection Systems (IDS) in order to ensure the security of the IIoT networks. Three different models were proposed to detect intrusions in the IIoT network by using deep learning architectures of Convolutional Neural Network (CNN), Long Short Term Memory (LSTM), and CNN + LSTM generated from a…

Citation impact

286
total citations
FWCI
55.04
Percentile
100%
References
55
Citations per year

Authors

2

Topics & keywords

Keywords
  • Computer science
  • Convolutional neural network
  • Intrusion detection system
  • Artificial intelligence
  • Internet of Things
  • Cloud computing
  • Class (philosophy)
  • Binary classification
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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